From f56273358a440dfd717a4d6a491099eaa1870728 Mon Sep 17 00:00:00 2001 From: amrit110 Date: Fri, 24 Nov 2023 11:25:32 -0500 Subject: [PATCH] deploy: b91653555e16192f342016763cb8c764f461dcff --- 404.html | 4 +- .../kaggle/heart_failure_prediction.ipynb.txt | 48 +- api/searchindex.js | 2 +- .../kaggle/heart_failure_prediction.html | 118 +- .../kaggle/heart_failure_prediction.ipynb | 510 +- .../kaggle/heart_failure_report_periodic.html | 207 +- .../mimiciv/mortality_prediction.html | 114 +- .../mimiciv/mortality_prediction.ipynb | 23170 +++++++++------- .../mimiciv/mortality_report_periodic.html | 151 +- api/tutorials/nihcxr/cxr_classification.html | 132 +- api/tutorials/nihcxr/cxr_classification.ipynb | 391 +- api/tutorials/nihcxr/monitor_api.html | 22 +- api/tutorials/nihcxr/monitor_api.ipynb | 128 +- .../nihcxr/nihcxr_report_periodic.html | 9 +- .../length_of_stay_report_periodic.html | 141 +- api/tutorials/synthea/los_prediction.html | 154 +- api/tutorials/synthea/los_prediction.ipynb | 3090 +-- ...8a0ec.101bc726.js => 1cd7c442.f735fc16.js} | 2 +- ...ee0c1.b6c646b2.js => 9f179204.8d399381.js} | 2 +- ...d370c.29f4916b.js => b91d99ed.37214bf2.js} | 2 +- assets/js/main.8bc6fff8.js | 2 + ...CENSE.txt => main.8bc6fff8.js.LICENSE.txt} | 0 assets/js/main.de3a9079.js | 2 - assets/js/runtime~main.49642ce9.js | 1 + assets/js/runtime~main.f74ffbd7.js | 1 - blog/archive/index.html | 4 +- blog/cyclops-alpha-release/index.html | 4 +- blog/index.html | 4 +- blog/tags/alpha/index.html | 4 +- blog/tags/index.html | 4 +- docs/intro/index.html | 4 +- index.html | 4 +- markdown-page/index.html | 4 +- 33 files changed, 15748 insertions(+), 12687 deletions(-) rename assets/js/{d098a0ec.101bc726.js => 1cd7c442.f735fc16.js} (64%) rename assets/js/{72bee0c1.b6c646b2.js => 9f179204.8d399381.js} (64%) rename assets/js/{3e9d370c.29f4916b.js => b91d99ed.37214bf2.js} (65%) create mode 100644 assets/js/main.8bc6fff8.js rename assets/js/{main.de3a9079.js.LICENSE.txt => main.8bc6fff8.js.LICENSE.txt} (100%) delete mode 100644 assets/js/main.de3a9079.js create mode 100644 assets/js/runtime~main.49642ce9.js delete mode 100644 assets/js/runtime~main.f74ffbd7.js diff --git a/404.html b/404.html index 950cff7fd..99bec5211 100644 --- a/404.html +++ b/404.html @@ -5,8 +5,8 @@ Page Not Found | CyclOps - - + +
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diff --git a/api/_sources/tutorials/kaggle/heart_failure_prediction.ipynb.txt b/api/_sources/tutorials/kaggle/heart_failure_prediction.ipynb.txt index d415fbe56..2722c0ba2 100644 --- a/api/_sources/tutorials/kaggle/heart_failure_prediction.ipynb.txt +++ b/api/_sources/tutorials/kaggle/heart_failure_prediction.ipynb.txt @@ -1232,49 +1232,11 @@ "shutil.copy(f\"{report_path}\", \".\")\n", "for i in range(4):\n", " report._model_card.overview = None\n", - " report._model_card.quantitative_analysis = None\n", - " results_flat = flatten_results_dict(\n", - " results=results,\n", - " remove_metrics=[\"BinaryROCCurve\", \"BinaryPrecisionRecallCurve\"],\n", - " model_name=model_name,\n", - " )\n", - "\n", - " for name, metric in results_female_flat.items():\n", - " split, name = name.split(\"/\") # noqa: PLW2901\n", - " descriptions = {\n", - " \"BinaryPrecision\": \"The proportion of predicted positive instances that are correctly predicted.\",\n", - " \"BinaryRecall\": \"The proportion of actual positive instances that are correctly predicted. Also known as recall or true positive rate.\",\n", - " \"BinaryAccuracy\": \"The proportion of all instances that are correctly predicted.\",\n", - " \"BinaryAUROC\": \"The area under the receiver operating characteristic curve (AUROC) is a measure of the performance of a binary classification model.\",\n", - " \"BinaryF1Score\": \"The harmonic mean of precision and recall.\",\n", - " }\n", - " report.log_quantitative_analysis(\n", - " \"performance\",\n", - " name=name,\n", - " value=np.clip(metric + np.random.normal(0, 0.1), 0, 1),\n", - " description=descriptions[name],\n", - " metric_slice=split,\n", - " pass_fail_thresholds=0.7,\n", - " pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold),\n", - " )\n", - "\n", - " for name, metric in results_flat.items():\n", - " split, name = name.split(\"/\") # noqa: PLW2901\n", - " descriptions = {\n", - " \"BinaryPrecision\": \"The proportion of predicted positive instances that are correctly predicted.\",\n", - " \"BinaryRecall\": \"The proportion of actual positive instances that are correctly predicted. Also known as recall or true positive rate.\",\n", - " \"BinaryAccuracy\": \"The proportion of all instances that are correctly predicted.\",\n", - " \"BinaryAUROC\": \"The area under the receiver operating characteristic curve (AUROC) is a measure of the performance of a binary classification model.\",\n", - " \"BinaryF1Score\": \"The harmonic mean of precision and recall.\",\n", - " }\n", - " report.log_quantitative_analysis(\n", - " \"performance\",\n", - " name=name,\n", - " value=np.clip(metric + np.random.normal(0, 0.1), 0, 1),\n", - " description=descriptions[name],\n", - " metric_slice=split,\n", - " pass_fail_thresholds=0.7,\n", - " pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold),\n", + " for metric in report._model_card.quantitative_analysis.performance_metrics:\n", + " metric.value = np.clip(\n", + " metric.value + np.random.normal(0, 0.1),\n", + " 0,\n", + " 1,\n", " )\n", " report_path = report.export(\n", " 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"Drop-NaNs-based-on-the-NAN_THRESHOLD"]], "Gender distribution": [[132, "Gender-distribution"], [135, "Gender-distribution"]], "Chest X-Ray Disease Classification": [[133, "Chest-X-Ray-Disease-Classification"]], "Generate Historical Reports": [[133, "Generate-Historical-Reports"]], "Initialize Periodic Report": [[133, "Initialize-Periodic-Report"]], "Load Dataset": [[133, "Load-Dataset"]], "Multilabel AUROC by Pathology and Sex": [[133, "Multilabel-AUROC-by-Pathology-and-Sex"]], "Multilabel AUROC by Pathology and Age": [[133, "Multilabel-AUROC-by-Pathology-and-Age"]], "Log Performance Metrics as Tests w/ Thresholds": [[133, "Log-Performance-Metrics-as-Tests-w/-Thresholds"]], "Populate Model Card Fields": [[133, "Populate-Model-Card-Fields"]], "NIHCXR Clinical Drift Experiments Tutorial": [[134, "NIHCXR-Clinical-Drift-Experiments-Tutorial"]], "Import Libraries and Load NIHCXR Dataset": [[134, "Import-Libraries-and-Load-NIHCXR-Dataset"]], "Example 1. Generate Source/Target Dataset for Experiments (1-2)": [[134, "Example-1.-Generate-Source/Target-Dataset-for-Experiments-(1-2)"]], "Example 2. Sensitivity test experiment with 3 dimensionality reduction techniques": [[134, "Example-2.-Sensitivity-test-experiment-with-3-dimensionality-reduction-techniques"]], "Example 3. Sensitivity test experiment with models trained on different datasets": [[134, "Example-3.-Sensitivity-test-experiment-with-models-trained-on-different-datasets"]], "Example 4. Sensitivity test experiment with different clinical shifts": [[134, "Example-4.-Sensitivity-test-experiment-with-different-clinical-shifts"]], "Example 5. Rolling window experiment with synthetic timestamps using biweekly window": [[134, "Example-5.-Rolling-window-experiment-with-synthetic-timestamps-using-biweekly-window"]], "Prolonged Length of Stay Prediction": [[135, "Prolonged-Length-of-Stay-Prediction"]], "Data Querying": [[135, "Data-Querying"]], "Compute length of stay (labels)": [[135, "Compute-length-of-stay-(labels)"]], "Length of stay distribution": [[135, "Length-of-stay-distribution"]], "monitor API": [[136, "monitor-api"]], "Example use cases": [[137, "example-use-cases"]], "Tabular data": [[137, "tabular-data"]], "Kaggle Heart Failure Prediction": [[137, "kaggle-heart-failure-prediction"]], "MIMICIV Mortality Prediction": [[137, "mimiciv-mortality-prediction"]], "Synthea Prolonged Length of Stay Prediction": [[137, "synthea-prolonged-length-of-stay-prediction"]], "Image data": [[137, "image-data"]], "NIH Chest X-ray classification": [[137, "nih-chest-x-ray-classification"]]}, "indexentries": 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Generate Source/Target Dataset for Experiments (1-2)": [[134, "Example-1.-Generate-Source/Target-Dataset-for-Experiments-(1-2)"]], "Example 2. Sensitivity test experiment with 3 dimensionality reduction techniques": [[134, "Example-2.-Sensitivity-test-experiment-with-3-dimensionality-reduction-techniques"]], "Example 3. Sensitivity test experiment with models trained on different datasets": [[134, "Example-3.-Sensitivity-test-experiment-with-models-trained-on-different-datasets"]], "Example 4. Sensitivity test experiment with different clinical shifts": [[134, "Example-4.-Sensitivity-test-experiment-with-different-clinical-shifts"]], "Example 5. Rolling window experiment with synthetic timestamps using biweekly window": [[134, "Example-5.-Rolling-window-experiment-with-synthetic-timestamps-using-biweekly-window"]], "Prolonged Length of Stay Prediction": [[135, "Prolonged-Length-of-Stay-Prediction"]], "Data Querying": [[135, "Data-Querying"]], "Compute length of stay (labels)": [[135, "Compute-length-of-stay-(labels)"]], "Length of stay distribution": [[135, "Length-of-stay-distribution"]], "monitor API": [[136, "monitor-api"]], "Example use cases": [[137, "example-use-cases"]], "Tabular data": [[137, "tabular-data"]], "Kaggle Heart Failure Prediction": [[137, "kaggle-heart-failure-prediction"]], "MIMICIV Mortality Prediction": [[137, "mimiciv-mortality-prediction"]], "Synthea Prolonged Length of Stay Prediction": [[137, "synthea-prolonged-length-of-stay-prediction"]], "Image data": [[137, "image-data"]], "NIH Chest X-ray classification": [[137, "nih-chest-x-ray-classification"]]}, "indexentries": 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"cyclops.report.report.ModelCardReport.log_regulation"]], "log_risk() (modelcardreport method)": [[121, "cyclops.report.report.ModelCardReport.log_risk"]], "log_use_case() (modelcardreport method)": [[121, "cyclops.report.report.ModelCardReport.log_use_case"]], "log_user() (modelcardreport method)": [[121, "cyclops.report.report.ModelCardReport.log_user"]], "log_version() (modelcardreport method)": [[121, "cyclops.report.report.ModelCardReport.log_version"]], "cyclops.tasks.classification": [[122, "module-cyclops.tasks.classification"]], "binarytabularclassificationtask (class in cyclops.tasks.classification)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask"]], "__init__() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.__init__"]], "add_model() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.add_model"]], "data_type (binarytabularclassificationtask property)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.data_type"]], "evaluate() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.evaluate"]], "get_model() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.get_model"]], "list_models() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.list_models"]], "list_models_params() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.list_models_params"]], "load_model() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.load_model"]], "models_count (binarytabularclassificationtask property)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.models_count"]], "predict() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.predict"]], "save_model() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.save_model"]], "task_type (binarytabularclassificationtask property)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.task_type"]], "train() (binarytabularclassificationtask method)": [[123, "cyclops.tasks.classification.BinaryTabularClassificationTask.train"]], "multilabelimageclassificationtask (class in cyclops.tasks.classification)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask"]], "__init__() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.__init__"]], "add_model() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.add_model"]], "data_type (multilabelimageclassificationtask property)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.data_type"]], "evaluate() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.evaluate"]], "get_model() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.get_model"]], "list_models() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.list_models"]], "list_models_params() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.list_models_params"]], "load_model() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.load_model"]], "models_count (multilabelimageclassificationtask property)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.models_count"]], "predict() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.predict"]], "save_model() (multilabelimageclassificationtask method)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.save_model"]], "task_type (multilabelimageclassificationtask property)": [[124, "cyclops.tasks.classification.MultilabelImageClassificationTask.task_type"]], "cyclops.data": [[125, "module-cyclops.data"]], "cyclops.data.features": [[125, "module-cyclops.data.features"]], "cyclops.evaluate": [[126, "module-cyclops.evaluate"]], "cyclops.evaluate.fairness": [[126, "module-cyclops.evaluate.fairness"]], "cyclops.evaluate.metrics": [[126, "module-cyclops.evaluate.metrics"]], "cyclops.evaluate.metrics.functional": [[126, "module-cyclops.evaluate.metrics.functional"]], "cyclops.monitor": [[127, "module-cyclops.monitor"]], "cyclops.report": [[128, "module-cyclops.report"]], "cyclops.tasks": [[129, "module-cyclops.tasks"]]}}) \ No newline at end of file diff --git a/api/tutorials/kaggle/heart_failure_prediction.html b/api/tutorials/kaggle/heart_failure_prediction.html index 6279be385..d17ff3555 100644 --- a/api/tutorials/kaggle/heart_failure_prediction.html +++ b/api/tutorials/kaggle/heart_failure_prediction.html @@ -485,7 +485,7 @@

Import Libraries 
-/mnt/data/poetry/pycyclops-wIzUAwxh-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+/mnt/data/poetry/pycyclops-mhx6UJW0-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
   from .autonotebook import tqdm as notebook_tqdm
@@ -557,7 +557,7 @@

Data Loading 
-2023-11-23 08:24:41,145 INFO cyclops.utils.file - Loading DataFrame from ./data/heart.csv
+2023-11-24 11:13:02,043 INFO cyclops.utils.file - Loading DataFrame from ./data/heart.csv
@@ -639,9 +639,9 @@

Sex values

-
+
@@ -1353,7 +1353,7 @@

Graphics

-
+
@@ -1361,7 +1361,7 @@

Graphics

-
+
@@ -1424,7 +1424,7 @@

Quantitative Analysis

- 0.8 + 0.71 @@ -1457,7 +1457,7 @@

Quantitative Analysis
- 0.9 + 1.0 @@ -1490,7 +1490,7 @@

Quantitative Analysis
- 0.85 + 0.9 @@ -1523,7 +1523,7 @@

Quantitative Analysis
- 0.99 + 1.0 @@ -1556,7 +1556,7 @@

Quantitative Analysis
- 0.84 + 0.6 @@ -1574,6 +1574,49 @@

Quantitative Analysis

+ + +
+

Graphics

+ +
+ + +
+ + + +
+ +
+ +
+ + + +
+ +
+ +
+ + + +
+ +
+ +
+ + +
+ + +
+ +
+ +
@@ -1614,7 +1657,7 @@

Graphics

-
+
@@ -1669,7 +1712,7 @@

Version

- Date: 2023-11-23 + Date: 2023-11-24
@@ -1887,8 +1930,8 @@

Model Parameters

-

Validation_fraction

- 0.1 +

Power_t

+ 0.5
@@ -1896,26 +1939,22 @@

Validation_fraction

-

Penalty

- l2 +

Shuffle

+ True
-
-

Learning_rate

- adaptive -
-

Class_weight

- balanced +

Learning_rate

+ adaptive
@@ -1923,8 +1962,8 @@

Class_weight

-

Epsilon

- 0.1 +

Class_weight

+ balanced
@@ -1932,8 +1971,8 @@

Epsilon

-

Power_t

- 0.5 +

Average

+ False
@@ -1941,8 +1980,8 @@

Power_t

-

Warm_start

- False +

Verbose

+ 0
@@ -1959,8 +1998,8 @@

Max_iter

-

Alpha

- 0.001 +

Epsilon

+ 0.1
@@ -1968,8 +2007,8 @@

Alpha

-

Eta0

- 0.01 +

Random_state

+ 123
@@ -1977,8 +2016,8 @@

Eta0

-

Random_state

- 123 +

Warm_start

+ False
@@ -1986,7 +2025,7 @@

Random_state

-

Shuffle

+

Fit_intercept

True
@@ -1995,8 +2034,8 @@

Shuffle

-

Average

- False +

Validation_fraction

+ 0.1
@@ -2004,7 +2043,7 @@

Average

-

Fit_intercept

+

Early_stopping

True
@@ -2012,14 +2051,18 @@

Fit_intercept

+
+

Alpha

+ 0.001 +
-

N_iter_no_change

- 5 +

Penalty

+ l2
@@ -2027,8 +2070,8 @@

N_iter_no_change

-

L1_ratio

- 0.15 +

Tol

+ 0.001
@@ -2036,8 +2079,8 @@

L1_ratio

-

Verbose

- 0 +

N_iter_no_change

+ 5
@@ -2054,8 +2097,8 @@

Loss

-

Early_stopping

- True +

L1_ratio

+ 0.15
@@ -2063,8 +2106,8 @@

Early_stopping

-

Tol

- 0.001 +

Eta0

+ 0.01
@@ -2366,7 +2409,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [11, 12, 13, 14, 15] - var histories = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9388452425942916\", \"0.7715498754845974\", \"0.7707471738924495\", \"0.8047192596079443\"], \"1\": [\"0.796875\", \"0.6473237331294894\", \"0.8904259730789965\", \"0.8876018804852451\", \"0.8136140274078921\"], \"2\": [\"0.8260869565217391\", \"0.7353343863368134\", \"1.0\", \"0.6544648927913362\", \"0.8210955737933718\"], \"3\": [\"0.6785714285714286\", \"0.7919668952937902\", \"0.6291783820910926\", \"0.5326082114183496\", \"0.5813701391072909\"], \"4\": [\"0.7450980392156863\", \"0.7644056435517494\", \"0.6853215239323296\", \"0.9626711874114409\", \"0.6702254333330125\"], \"5\": [\"0.8819444444444444\", \"0.994280029220096\", \"0.9571455905998957\", \"1.0\", \"0.7405786835226612\"], \"6\": [\"0.8623853211009175\", \"0.9172910829625154\", \"0.7657936656898735\", \"0.807871635560329\", \"0.7623651469403532\"], \"7\": [\"0.8676470588235294\", \"0.8135356598294874\", \"0.9450972604455096\", \"0.8268379025565245\", \"0.8626006007692846\"], \"8\": [\"0.9076923076923077\", \"0.9832478504674755\", \"1.0\", \"0.7961972386510326\", \"0.9014257673033106\"], \"9\": [\"0.8872180451127819\", \"0.9594326314640675\", \"0.9370363304040299\", \"0.9186284118847525\", \"0.7714923619447597\"], \"10\": [\"0.927972027972028\", \"0.8113611118890558\", \"0.9144437731851586\", \"0.9698325116171631\", \"0.9302504901737985\"], \"11\": [\"0.842391304347826\", \"0.9193114683535377\", \"0.9864783970277446\", \"0.7658222453419492\", \"0.7960421624802183\"], \"12\": [\"0.8686868686868687\", \"0.9556311389295675\", \"0.8807940946251006\", \"0.8053572715828856\", \"0.8970872746375872\"], \"13\": [\"0.8431372549019608\", \"0.8502327170958246\", \"0.7896432133785524\", \"0.9211576269580154\", \"0.8532945318236702\"], \"14\": [\"0.8557213930348259\", \"0.8164620859125082\", \"0.6723061832241325\", \"0.967304897158582\", \"0.990864550321209\"], \"15\": [\"0.9152319464371114\", \"0.8854306465584685\", \"0.8334144524161107\", \"0.8987415298849972\", \"0.8371863032723775\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8421052631578947\", \"1.0\", \"1.0\", \"0.915029695471783\", \"0.8854227199246666\"], \"1\": [\"0.796875\", \"0.9919385585353486\", \"0.9946577698769941\", \"1.0\", \"1.0\"], \"2\": [\"0.8260869565217391\", \"0.7791735634138384\", \"0.7361794759259214\", \"0.6637711983856686\", \"0.8492747575572651\"], \"3\": [\"0.6785714285714286\", \"0.7349141241505789\", \"0.6506482245446827\", \"0.5340384515844391\", \"0.5962424134969672\"], \"4\": [\"0.7450980392156863\", \"0.749871238584802\", \"0.6806186088648097\", \"0.7029628905458104\", \"0.48266279770789233\"], \"5\": [\"0.8819444444444444\", \"0.9421074101446135\", \"0.9449605616784943\", \"0.9659403151543672\", \"0.8750350710495738\"], \"6\": [\"0.8623853211009175\", \"1.0\", \"0.9636390887760267\", \"0.9497848408413192\", \"0.8622753529425798\"], \"7\": [\"0.8676470588235294\", \"0.9138119245411664\", \"0.949523660604063\", \"0.9495041804447839\", \"1.0\"], \"8\": [\"0.9076923076923077\", \"0.8246041361147964\", \"0.8105302874620731\", \"0.9606215148160199\", \"0.9047802046146495\"], \"9\": [\"0.8872180451127819\", \"0.8949539233306965\", \"0.9671811054211867\", \"1.0\", \"0.9820965257002248\"], \"10\": [\"0.927972027972028\", \"0.9470545772243185\", \"1.0\", \"0.8827269667133483\", \"0.7908747856531504\"], \"11\": [\"0.842391304347826\", \"0.7688468661069753\", \"0.7669910936596005\", \"0.8372392681204278\", \"0.7081580620963568\"], \"12\": [\"0.8686868686868687\", \"0.9956847539282012\", \"0.9780280982854744\", \"1.0\", \"1.0\"], \"13\": [\"0.8431372549019608\", \"0.7390753216035594\", \"0.7240150394812629\", \"0.6953490064151775\", \"0.9047196566719026\"], \"14\": [\"0.8557213930348259\", \"0.968955119297434\", \"1.0\", \"0.9757272482787275\", \"1.0\"], \"15\": [\"0.9152319464371114\", \"0.8564523022715463\", \"0.8447313905909526\", \"0.7185590966888746\", \"0.5999692893957338\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2647,10 +2690,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"Sex:F\", \"Age:overall_Age\"], \"1\": [\"metric:Accuracy\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"2\": [\"metric:Precision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"3\": [\"metric:Recall\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"4\": [\"metric:F1 Score\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"5\": [\"metric:AUROC\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"6\": [\"metric:Accuracy\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"7\": [\"metric:Precision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"8\": [\"metric:Recall\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"9\": [\"metric:F1 Score\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"10\": [\"metric:AUROC\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"11\": [\"metric:Accuracy\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"12\": [\"metric:Precision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"13\": [\"metric:Recall\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"14\": [\"metric:F1 Score\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"15\": [\"metric:AUROC\", \"Sex:overall_Sex\", \"Age:overall_Age\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9388452425942916\", \"0.7715498754845974\", \"0.7707471738924495\", \"0.8047192596079443\"], \"1\": [\"0.796875\", \"0.6473237331294894\", \"0.8904259730789965\", \"0.8876018804852451\", \"0.8136140274078921\"], \"2\": [\"0.8260869565217391\", \"0.7353343863368134\", \"1.0\", \"0.6544648927913362\", \"0.8210955737933718\"], \"3\": [\"0.6785714285714286\", \"0.7919668952937902\", \"0.6291783820910926\", \"0.5326082114183496\", \"0.5813701391072909\"], \"4\": [\"0.7450980392156863\", \"0.7644056435517494\", \"0.6853215239323296\", \"0.9626711874114409\", \"0.6702254333330125\"], \"5\": [\"0.8819444444444444\", \"0.994280029220096\", \"0.9571455905998957\", \"1.0\", \"0.7405786835226612\"], \"6\": [\"0.8623853211009175\", \"0.9172910829625154\", \"0.7657936656898735\", \"0.807871635560329\", \"0.7623651469403532\"], \"7\": [\"0.8676470588235294\", \"0.8135356598294874\", \"0.9450972604455096\", \"0.8268379025565245\", \"0.8626006007692846\"], \"8\": [\"0.9076923076923077\", \"0.9832478504674755\", \"1.0\", \"0.7961972386510326\", \"0.9014257673033106\"], \"9\": [\"0.8872180451127819\", \"0.9594326314640675\", \"0.9370363304040299\", \"0.9186284118847525\", \"0.7714923619447597\"], \"10\": [\"0.927972027972028\", \"0.8113611118890558\", \"0.9144437731851586\", \"0.9698325116171631\", \"0.9302504901737985\"], \"11\": [\"0.842391304347826\", \"0.9193114683535377\", \"0.9864783970277446\", \"0.7658222453419492\", \"0.7960421624802183\"], \"12\": [\"0.8686868686868687\", \"0.9556311389295675\", \"0.8807940946251006\", \"0.8053572715828856\", \"0.8970872746375872\"], \"13\": [\"0.8431372549019608\", \"0.8502327170958246\", \"0.7896432133785524\", \"0.9211576269580154\", \"0.8532945318236702\"], \"14\": [\"0.8557213930348259\", \"0.8164620859125082\", \"0.6723061832241325\", \"0.967304897158582\", \"0.990864550321209\"], \"15\": [\"0.9152319464371114\", \"0.8854306465584685\", \"0.8334144524161107\", \"0.8987415298849972\", \"0.8371863032723775\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"1.0\", \"1.0\", \"0.915029695471783\", \"0.8854227199246666\"], \"1\": [\"0.796875\", \"0.9919385585353486\", \"0.9946577698769941\", \"1.0\", \"1.0\"], \"2\": [\"0.8260869565217391\", \"0.7791735634138384\", \"0.7361794759259214\", \"0.6637711983856686\", \"0.8492747575572651\"], \"3\": [\"0.6785714285714286\", \"0.7349141241505789\", \"0.6506482245446827\", \"0.5340384515844391\", \"0.5962424134969672\"], \"4\": [\"0.7450980392156863\", \"0.749871238584802\", \"0.6806186088648097\", \"0.7029628905458104\", \"0.48266279770789233\"], \"5\": [\"0.8819444444444444\", \"0.9421074101446135\", \"0.9449605616784943\", \"0.9659403151543672\", \"0.8750350710495738\"], \"6\": [\"0.8623853211009175\", \"1.0\", \"0.9636390887760267\", \"0.9497848408413192\", \"0.8622753529425798\"], \"7\": [\"0.8676470588235294\", \"0.9138119245411664\", \"0.949523660604063\", \"0.9495041804447839\", \"1.0\"], \"8\": [\"0.9076923076923077\", \"0.8246041361147964\", \"0.8105302874620731\", \"0.9606215148160199\", \"0.9047802046146495\"], \"9\": [\"0.8872180451127819\", \"0.8949539233306965\", \"0.9671811054211867\", \"1.0\", \"0.9820965257002248\"], \"10\": [\"0.927972027972028\", \"0.9470545772243185\", \"1.0\", \"0.8827269667133483\", \"0.7908747856531504\"], \"11\": [\"0.842391304347826\", \"0.7688468661069753\", \"0.7669910936596005\", \"0.8372392681204278\", \"0.7081580620963568\"], \"12\": [\"0.8686868686868687\", \"0.9956847539282012\", \"0.9780280982854744\", \"1.0\", \"1.0\"], \"13\": [\"0.8431372549019608\", \"0.7390753216035594\", \"0.7240150394812629\", \"0.6953490064151775\", \"0.9047196566719026\"], \"14\": [\"0.8557213930348259\", \"0.968955119297434\", \"1.0\", \"0.9757272482787275\", \"1.0\"], \"15\": [\"0.9152319464371114\", \"0.8564523022715463\", \"0.8447313905909526\", \"0.7185590966888746\", \"0.5999692893957338\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"positive\", \"2\": \"neutral\", \"3\": \"negative\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"neutral\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"neutral\", \"14\": \"positive\", \"15\": \"negative\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": false, \"4\": false, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"neutral\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"neutral\", \"6\": \"neutral\", \"7\": \"positive\", \"8\": \"positive\", \"9\": \"positive\", \"10\": \"negative\", \"11\": \"negative\", \"12\": \"positive\", \"13\": \"neutral\", \"14\": \"positive\", \"15\": \"negative\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": false, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Accuracy\", \"2\": \"Precision\", \"3\": \"Recall\", \"4\": \"F1 Score\", \"5\": \"AUROC\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"Accuracy\", \"12\": \"Precision\", \"13\": \"Recall\", \"14\": \"F1 Score\", \"15\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2923,10 +2966,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"Sex:F\", \"Age:overall_Age\"], \"1\": [\"metric:Accuracy\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"2\": [\"metric:Precision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"3\": [\"metric:Recall\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"4\": [\"metric:F1 Score\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"5\": [\"metric:AUROC\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"6\": [\"metric:Accuracy\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"7\": [\"metric:Precision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"8\": [\"metric:Recall\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"9\": [\"metric:F1 Score\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"10\": [\"metric:AUROC\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"11\": [\"metric:Accuracy\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"12\": [\"metric:Precision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"13\": [\"metric:Recall\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"14\": [\"metric:F1 Score\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"15\": [\"metric:AUROC\", \"Sex:overall_Sex\", \"Age:overall_Age\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9388452425942916\", \"0.7715498754845974\", \"0.7707471738924495\", \"0.8047192596079443\"], \"1\": [\"0.796875\", \"0.6473237331294894\", \"0.8904259730789965\", \"0.8876018804852451\", \"0.8136140274078921\"], \"2\": [\"0.8260869565217391\", \"0.7353343863368134\", \"1.0\", \"0.6544648927913362\", \"0.8210955737933718\"], \"3\": [\"0.6785714285714286\", \"0.7919668952937902\", \"0.6291783820910926\", \"0.5326082114183496\", \"0.5813701391072909\"], \"4\": [\"0.7450980392156863\", \"0.7644056435517494\", \"0.6853215239323296\", \"0.9626711874114409\", \"0.6702254333330125\"], \"5\": [\"0.8819444444444444\", \"0.994280029220096\", \"0.9571455905998957\", \"1.0\", \"0.7405786835226612\"], \"6\": [\"0.8623853211009175\", \"0.9172910829625154\", \"0.7657936656898735\", \"0.807871635560329\", \"0.7623651469403532\"], \"7\": [\"0.8676470588235294\", \"0.8135356598294874\", \"0.9450972604455096\", \"0.8268379025565245\", \"0.8626006007692846\"], \"8\": [\"0.9076923076923077\", \"0.9832478504674755\", \"1.0\", \"0.7961972386510326\", \"0.9014257673033106\"], \"9\": [\"0.8872180451127819\", \"0.9594326314640675\", \"0.9370363304040299\", \"0.9186284118847525\", \"0.7714923619447597\"], \"10\": [\"0.927972027972028\", \"0.8113611118890558\", \"0.9144437731851586\", \"0.9698325116171631\", \"0.9302504901737985\"], \"11\": [\"0.842391304347826\", \"0.9193114683535377\", \"0.9864783970277446\", \"0.7658222453419492\", \"0.7960421624802183\"], \"12\": [\"0.8686868686868687\", \"0.9556311389295675\", \"0.8807940946251006\", \"0.8053572715828856\", \"0.8970872746375872\"], \"13\": [\"0.8431372549019608\", \"0.8502327170958246\", \"0.7896432133785524\", \"0.9211576269580154\", \"0.8532945318236702\"], \"14\": [\"0.8557213930348259\", \"0.8164620859125082\", \"0.6723061832241325\", \"0.967304897158582\", \"0.990864550321209\"], \"15\": [\"0.9152319464371114\", \"0.8854306465584685\", \"0.8334144524161107\", \"0.8987415298849972\", \"0.8371863032723775\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"1.0\", \"1.0\", \"0.915029695471783\", \"0.8854227199246666\"], \"1\": [\"0.796875\", \"0.9919385585353486\", \"0.9946577698769941\", \"1.0\", \"1.0\"], \"2\": [\"0.8260869565217391\", \"0.7791735634138384\", \"0.7361794759259214\", \"0.6637711983856686\", \"0.8492747575572651\"], \"3\": [\"0.6785714285714286\", \"0.7349141241505789\", \"0.6506482245446827\", \"0.5340384515844391\", \"0.5962424134969672\"], \"4\": [\"0.7450980392156863\", \"0.749871238584802\", \"0.6806186088648097\", \"0.7029628905458104\", \"0.48266279770789233\"], \"5\": [\"0.8819444444444444\", \"0.9421074101446135\", \"0.9449605616784943\", \"0.9659403151543672\", \"0.8750350710495738\"], \"6\": [\"0.8623853211009175\", \"1.0\", \"0.9636390887760267\", \"0.9497848408413192\", \"0.8622753529425798\"], \"7\": [\"0.8676470588235294\", \"0.9138119245411664\", \"0.949523660604063\", \"0.9495041804447839\", \"1.0\"], \"8\": [\"0.9076923076923077\", \"0.8246041361147964\", \"0.8105302874620731\", \"0.9606215148160199\", \"0.9047802046146495\"], \"9\": [\"0.8872180451127819\", \"0.8949539233306965\", \"0.9671811054211867\", \"1.0\", \"0.9820965257002248\"], \"10\": [\"0.927972027972028\", \"0.9470545772243185\", \"1.0\", \"0.8827269667133483\", \"0.7908747856531504\"], \"11\": [\"0.842391304347826\", \"0.7688468661069753\", \"0.7669910936596005\", \"0.8372392681204278\", \"0.7081580620963568\"], \"12\": [\"0.8686868686868687\", \"0.9956847539282012\", \"0.9780280982854744\", \"1.0\", \"1.0\"], \"13\": [\"0.8431372549019608\", \"0.7390753216035594\", \"0.7240150394812629\", \"0.6953490064151775\", \"0.9047196566719026\"], \"14\": [\"0.8557213930348259\", \"0.968955119297434\", \"1.0\", \"0.9757272482787275\", \"1.0\"], \"15\": [\"0.9152319464371114\", \"0.8564523022715463\", \"0.8447313905909526\", \"0.7185590966888746\", \"0.5999692893957338\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"positive\", \"2\": \"neutral\", \"3\": \"negative\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"neutral\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"neutral\", \"14\": \"positive\", \"15\": \"negative\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": false, \"4\": false, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"neutral\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"neutral\", \"6\": \"neutral\", \"7\": \"positive\", \"8\": \"positive\", \"9\": \"positive\", \"10\": \"negative\", \"11\": \"negative\", \"12\": \"positive\", \"13\": \"neutral\", \"14\": \"positive\", \"15\": \"negative\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": false, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Accuracy\", \"2\": \"Precision\", \"3\": \"Recall\", \"4\": \"F1 Score\", \"5\": \"AUROC\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"Accuracy\", \"12\": \"Precision\", \"13\": \"Recall\", \"14\": \"F1 Score\", \"15\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); diff --git a/api/tutorials/mimiciv/mortality_prediction.html b/api/tutorials/mimiciv/mortality_prediction.html index de782e9a2..8f979cbeb 100644 --- a/api/tutorials/mimiciv/mortality_prediction.html +++ b/api/tutorials/mimiciv/mortality_prediction.html @@ -489,7 +489,7 @@

Import Libraries 
-/mnt/data/poetry/pycyclops-wIzUAwxh-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+/mnt/data/poetry/pycyclops-mhx6UJW0-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
   from .autonotebook import tqdm as notebook_tqdm

@@ -713,9 +713,9 @@

Compute mortality (labels) 
-2023-11-23 08:25:00,453 INFO cycquery.orm    - Database setup, ready to run queries!
-2023-11-23 08:25:07,192 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:25:07,193 INFO cycquery.utils.profile - Finished executing function run_query in 4.665388 s
+2023-11-24 11:13:20,676 INFO cycquery.orm    - Database setup, ready to run queries!
+2023-11-24 11:13:27,279 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:13:27,280 INFO cycquery.utils.profile - Finished executing function run_query in 4.665870 s

@@ -734,8 +734,8 @@

Compute mortality (labels) 
-2023-11-23 08:25:38,731 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:25:38,732 INFO cycquery.utils.profile - Finished executing function run_query in 30.676140 s
+2023-11-24 11:13:56,012 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:13:56,013 INFO cycquery.utils.profile - Finished executing function run_query in 27.885787 s

@@ -800,9 +800,9 @@

Drop NaNs based on the

-
+
@@ -1417,7 +1417,7 @@

Graphics

-
+
@@ -1425,7 +1425,7 @@

Graphics

-
+
@@ -1433,7 +1433,7 @@

Graphics

-
+
@@ -1514,7 +1514,7 @@

Quantitative Analysis

- 1.0 + 0.97 @@ -1547,7 +1547,7 @@

Quantitative Analysis
- 0.05 + 0.54 @@ -1580,7 +1580,7 @@

Quantitative Analysis
- 0.0 + 0.17 @@ -1646,7 +1646,7 @@

Quantitative Analysis
- 0.75 + 0.99 @@ -1719,7 +1719,7 @@

Quantitative Analysis
- 0.9 + 0.88 @@ -1752,7 +1752,7 @@

Quantitative Analysis
- 0.08 + 0.51 @@ -1785,7 +1785,7 @@

Quantitative Analysis
- 0.0 + 0.13 @@ -1818,7 +1818,7 @@

Quantitative Analysis
- 0.06 + 0.23 @@ -1851,7 +1851,7 @@

Quantitative Analysis
- 0.73 + 0.91 @@ -1869,6 +1869,9 @@

Quantitative Analysis

+ + +
@@ -1909,7 +1912,7 @@

Graphics

-
+
@@ -1964,7 +1967,7 @@

Version

- Date: 2023-11-23 + Date: 2023-11-24
@@ -2191,10 +2194,6 @@

Model Parameters

-
-

Gamma

- 10 -
@@ -2205,24 +2204,20 @@

Gamma

+
+

Random_state

+ 123 +
-
-

Objective

- binary:logistic -
-
-

Random_state

- 123 -
@@ -2238,6 +2233,19 @@

Random_state

+
+

Gamma

+ 0 +
+ + + + + +
+

Max_depth

+ 2 +
@@ -2268,10 +2276,6 @@

Random_state

-
-

Missing

- nan -
@@ -2288,8 +2292,8 @@

Missing

-

Seed

- 123 +

Missing

+ nan
@@ -2301,6 +2305,10 @@

Seed

+
+

N_estimators

+ 250 +
@@ -2312,18 +2320,14 @@

Seed

-

Colsample_bytree

- 0.8 +

Min_child_weight

+ 3
-
-

Enable_categorical

- False -
@@ -2340,8 +2344,8 @@

Enable_categorical

-

N_estimators

- 500 +

Seed

+ 123
@@ -2349,8 +2353,8 @@

N_estimators

-

Reg_lambda

- 10 +

Eval_metric

+ logloss
@@ -2363,8 +2367,8 @@

Reg_lambda

-

Eval_metric

- logloss +

Reg_lambda

+ 0
@@ -2377,8 +2381,8 @@

Eval_metric

-

Max_depth

- 5 +

Learning_rate

+ 0.1
@@ -2390,11 +2394,10 @@

Max_depth

- - - - - +
+

Enable_categorical

+ False +
@@ -2406,14 +2409,18 @@

Max_depth

-

Learning_rate

- 0.01 +

Colsample_bytree

+ 0.7
+
+

Objective

+ binary:logistic +
@@ -2424,10 +2431,6 @@

Learning_rate

-
-

Min_child_weight

- 3 -
@@ -2703,7 +2706,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [20, 21, 22, 23, 24, 45, 46, 47, 48, 49] - var histories = JSON.parse("{\"0\": [\"0.9938556067588326\", \"1.0\", \"1.0\", \"1.0\", \"0.9624791516577729\", \"0.9684155793292565\", \"1.0\", \"0.9322132496657871\"], \"1\": [\"0.0\", \"0.09971832307720793\", \"0.0\", \"0.0\", \"0.038443657820264196\", \"0.0\", \"0.07858249637040482\", \"0.061570421819291135\"], \"2\": [\"0.0\", \"0.0\", \"0.21979967941589065\", \"0.15202165141211327\", \"0.0\", \"0.0\", \"0.078096307870897\", \"0.0\"], \"3\": [\"0.0\", \"0.0\", \"0.09105647730583516\", \"0.0\", \"0.0\", \"0.22316854841702705\", \"0.0\", \"0.0\"], \"4\": [\"0.7482612055641422\", \"0.719862989681311\", \"0.7445177672186913\", \"0.7831315648403597\", \"0.6248692306176002\", \"0.9026667908500056\", \"0.7483615351710936\", \"0.6968843874934543\"], \"5\": [\"0.9868184541641701\", \"0.9561559632039621\", \"1.0\", \"0.8890350948324139\", \"0.9061253253169075\", \"1.0\", \"0.9554172251312234\", \"1.0\"], \"6\": [\"0.0\", \"0.11621016177733319\", \"0.0\", \"0.0025444729693200447\", \"0.10367468378142052\", \"0.0\", \"0.008875244086175444\", \"0.10673727865066363\"], \"7\": [\"0.0\", \"0.027138301602683376\", \"0.0\", \"0.0\", \"0.037976948609530936\", \"0.06422998127948823\", \"0.006593106121994086\", \"0.0\"], \"8\": [\"0.0\", \"0.0\", \"0.0076989604074267325\", \"0.04042806262160304\", \"0.0991827754307281\", \"0.0\", \"0.13649589008489377\", \"0.09380571831467463\"], \"9\": [\"0.8595380029806259\", \"0.7691904349721002\", \"0.9600788839291399\", \"0.8282775995129016\", \"0.878776435670868\", \"0.9333389163458563\", \"0.9787477386465779\", \"0.878917157319109\"], \"10\": [\"0.9755571531272466\", \"1.0\", \"1.0\", \"1.0\", \"0.9318934530955364\", \"1.0\", \"0.9078569142260178\", \"1.0\"], \"11\": [\"0.0\", \"0.0\", \"0.0\", \"0.08487166865765733\", \"0.07691937885651284\", \"0.14122120553678105\", \"0.0\", \"0.0\"], \"12\": [\"0.0\", \"0.047747879045533514\", \"0.0\", \"0.1224542067698369\", \"0.14397548239768707\", \"0.20318834352718707\", \"0.0\", \"0.03138137418675985\"], \"13\": [\"0.0\", \"0.0\", \"0.02800493604075518\", \"0.0\", \"0.0\", \"0.01789939217816505\", \"0.07106448031583336\", \"0.06673015341839304\"], \"14\": [\"0.8030148684381637\", \"0.6791560389729489\", \"0.8372962075729853\", \"0.962354749685657\", \"0.7362284586425828\", \"0.5678681660695661\", \"0.5500755630591415\", \"0.8362123392050905\"], \"15\": [\"0.9883720930232558\", \"1.0\", \"1.0\", \"0.7893196672803455\", \"1.0\", \"0.9835823483012499\", \"1.0\", \"0.7203832895438956\"], \"16\": [\"0.0\", \"0.0\", \"0.09578782265189635\", \"0.047638197685841994\", \"0.0\", \"0.14137367216595606\", \"0.0\", \"0.12197535771823882\"], \"17\": [\"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.011236234587489465\", \"0.030128043374910665\"], \"18\": [\"0.0\", \"0.0059083967835457185\", \"0.0\", \"0.0\", \"0.04178778860280271\", \"0.08787351815107622\", \"0.012956583022895492\", \"0.0007738551289361559\"], \"19\": [\"0.8488703439853451\", \"0.9127310386437131\", \"0.7796661407050053\", \"0.7282146766614328\", \"0.9307617989220323\", \"0.6979642133505481\", \"0.858507492541033\", \"0.9223149963128429\"], \"20\": [\"0.982124079915878\", \"0.9456210314817315\", \"1.0\", \"0.9577191324952529\", \"0.9764907964257965\", \"0.8505876630607123\", \"0.9759570070982758\", \"1.0\"], \"21\": [\"0.0\", \"0.0\", \"0.16498694780973078\", \"0.10178726506486496\", \"0.0\", \"0.0\", \"0.1214325068997815\", \"0.045606091153573176\"], \"22\": [\"0.0\", \"0.12459881244704388\", \"0.0\", \"0.0\", \"0.10071970835634388\", \"0.028781611018928368\", \"0.0\", \"0.0\"], \"23\": [\"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.030089728851838776\", \"0.0\", \"0.0\", \"0.0\"], \"24\": [\"0.8262060712936137\", \"0.882856522862133\", \"0.6536468342491204\", \"0.870719989604237\", \"0.8098316461099845\", \"0.9463595020554448\", \"0.9325249457459681\", \"0.7538263217935368\"], \"25\": [\"0.9938556067588326\", \"1.0\", \"1.0\", \"1.0\", \"0.9624791516577729\", \"0.9684155793292565\", \"1.0\", \"0.9322132496657871\", \"0.9562372812203237\"], \"26\": [\"0.0\", \"0.09971832307720793\", \"0.0\", \"0.0\", \"0.038443657820264196\", \"0.0\", \"0.07858249637040482\", \"0.061570421819291135\", \"0.0\"], \"27\": [\"0.0\", \"0.0\", \"0.21979967941589065\", \"0.15202165141211327\", \"0.0\", \"0.0\", \"0.078096307870897\", \"0.0\", \"0.0\"], \"28\": [\"0.0\", \"0.0\", \"0.09105647730583516\", \"0.0\", \"0.0\", \"0.22316854841702705\", \"0.0\", \"0.0\", \"0.04532526103716064\"], \"29\": [\"0.7482612055641422\", \"0.719862989681311\", \"0.7445177672186913\", \"0.7831315648403597\", \"0.6248692306176002\", \"0.9026667908500056\", \"0.7483615351710936\", \"0.6968843874934543\", \"0.7563975419116553\"], \"30\": [\"0.9868184541641701\", \"0.9561559632039621\", \"1.0\", \"0.8890350948324139\", \"0.9061253253169075\", \"1.0\", \"0.9554172251312234\", \"1.0\", \"1.0\"], \"31\": [\"0.0\", \"0.11621016177733319\", \"0.0\", \"0.0025444729693200447\", \"0.10367468378142052\", \"0.0\", \"0.008875244086175444\", \"0.10673727865066363\", \"0.0\"], \"32\": [\"0.0\", \"0.027138301602683376\", \"0.0\", \"0.0\", \"0.037976948609530936\", \"0.06422998127948823\", \"0.006593106121994086\", \"0.0\", \"0.10532519537736414\"], \"33\": [\"0.0\", \"0.0\", \"0.0076989604074267325\", \"0.04042806262160304\", \"0.0991827754307281\", \"0.0\", \"0.13649589008489377\", \"0.09380571831467463\", \"0.0988430051703231\"], \"34\": [\"0.8595380029806259\", \"0.7691904349721002\", \"0.9600788839291399\", \"0.8282775995129016\", \"0.878776435670868\", \"0.9333389163458563\", \"0.9787477386465779\", \"0.878917157319109\", \"0.9432769130880525\"], \"35\": [\"0.9755571531272466\", \"1.0\", \"1.0\", \"1.0\", \"0.9318934530955364\", \"1.0\", \"0.9078569142260178\", \"1.0\", \"0.9288170044221256\"], \"36\": [\"0.0\", \"0.0\", \"0.0\", \"0.08487166865765733\", \"0.07691937885651284\", \"0.14122120553678105\", \"0.0\", \"0.0\", \"0.08950538352460372\"], \"37\": [\"0.0\", \"0.047747879045533514\", \"0.0\", \"0.1224542067698369\", \"0.14397548239768707\", \"0.20318834352718707\", \"0.0\", \"0.03138137418675985\", \"0.07175049133610613\"], \"38\": [\"0.0\", \"0.0\", \"0.02800493604075518\", \"0.0\", \"0.0\", \"0.01789939217816505\", \"0.07106448031583336\", \"0.06673015341839304\", \"0.08953128034808681\"], \"39\": [\"0.8030148684381637\", \"0.6791560389729489\", \"0.8372962075729853\", \"0.962354749685657\", \"0.7362284586425828\", \"0.5678681660695661\", \"0.5500755630591415\", \"0.8362123392050905\", \"0.8968793124468617\"], \"40\": [\"0.9883720930232558\", \"1.0\", \"1.0\", \"0.7893196672803455\", \"1.0\", \"0.9835823483012499\", \"1.0\", \"0.7203832895438956\", \"1.0\"], \"41\": [\"0.0\", \"0.0\", \"0.09578782265189635\", \"0.047638197685841994\", \"0.0\", \"0.14137367216595606\", \"0.0\", \"0.12197535771823882\", \"0.0\"], \"42\": [\"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.011236234587489465\", \"0.030128043374910665\", \"0.02841367550252792\"], \"43\": [\"0.0\", \"0.0059083967835457185\", \"0.0\", \"0.0\", \"0.04178778860280271\", \"0.08787351815107622\", \"0.012956583022895492\", \"0.0007738551289361559\", \"0.07247702997288386\"], \"44\": [\"0.8488703439853451\", \"0.9127310386437131\", \"0.7796661407050053\", \"0.7282146766614328\", \"0.9307617989220323\", \"0.6979642133505481\", \"0.858507492541033\", \"0.9223149963128429\", \"0.7766476570651996\"], \"45\": [\"0.982124079915878\", \"0.9456210314817315\", \"1.0\", \"0.9577191324952529\", \"0.9764907964257965\", \"0.8505876630607123\", \"0.9759570070982758\", \"1.0\", \"0.8980457855125427\"], \"46\": [\"0.0\", \"0.0\", \"0.16498694780973078\", \"0.10178726506486496\", \"0.0\", \"0.0\", \"0.1214325068997815\", \"0.045606091153573176\", \"0.0800467534922995\"], \"47\": [\"0.0\", \"0.12459881244704388\", \"0.0\", \"0.0\", \"0.10071970835634388\", \"0.028781611018928368\", \"0.0\", \"0.0\", \"0.0\"], \"48\": [\"0.0\", \"0.0\", \"0.0\", \"0.0\", \"0.030089728851838776\", \"0.0\", \"0.0\", \"0.0\", \"0.06429407099940196\"], \"49\": [\"0.8262060712936137\", \"0.882856522862133\", \"0.6536468342491204\", \"0.870719989604237\", \"0.8098316461099845\", \"0.9463595020554448\", \"0.9325249457459681\", \"0.7538263217935368\", \"0.7300461954914608\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9942279942279942\", \"0.7594144965282804\", \"0.9529435179909627\", \"1.0\", \"0.9824222087172482\", \"0.8918760706294051\", \"1.0\", \"0.9192617580826633\"], \"1\": [\"0.0\", \"0.039238992815548435\", \"0.0\", \"0.055517905809275285\", \"0.0\", \"0.13421211539934277\", \"0.0\", \"0.04463031659295377\"], \"2\": [\"0.0\", \"0.0\", \"0.08711249881031106\", \"0.07241396632645575\", \"0.08128642675685682\", \"0.02902037431332784\", \"0.0\", \"0.04474303889930112\"], \"3\": [\"0.0\", \"0.02205527619535966\", \"0.03243902948582891\", \"0.03494230964539643\", \"0.0\", \"0.0\", \"0.024057418374333433\", \"0.11112365920573815\"], \"4\": [\"0.7873730043541365\", \"0.8490645002357041\", \"0.8284713265874177\", \"0.7725107538646363\", \"0.8669065970069708\", \"0.7330137201245794\", \"0.7150319244733144\", \"0.6964042400231425\"], \"5\": [\"0.9855072463768116\", \"0.9476931593826841\", \"0.9879239618756389\", \"1.0\", \"0.9746544306089349\", \"0.7902046471798005\", \"0.7976488988761291\", \"0.9494576043250694\"], \"6\": [\"0.5\", \"0.3678441498661924\", \"0.5292269735666868\", \"0.5305294150629818\", \"0.35836260429896805\", \"0.47847272137702107\", \"0.55514972590488\", \"0.37351242736419443\"], \"7\": [\"0.17391304347826086\", \"0.3320907228868427\", \"0.36502179115312994\", \"0.0\", \"0.00271057995514265\", \"0.17106348095286344\", \"0.2809067739249912\", \"0.146257989720016\"], \"8\": [\"0.25806451612903225\", \"0.24223931150711597\", \"0.11546244070507433\", \"0.017291302768986883\", \"0.20669981383759975\", \"0.16472540906888358\", \"0.35577441497030965\", \"0.3178680487264552\"], \"9\": [\"0.9082341821416657\", \"0.76426587141965\", \"1.0\", \"0.8561398085736192\", \"0.92943589011621\", \"0.8058255388359045\", \"0.8074467931292719\", \"0.8775635640987218\"], \"10\": [\"0.9785819793205317\", \"0.925754895225367\", \"1.0\", \"0.9249110470119646\", \"0.9902885546536232\", \"0.9217424791342514\", \"1.0\", \"1.0\"], \"11\": [\"0.8\", \"0.890978490101253\", \"0.9750319727760646\", \"0.7578298434530611\", \"0.6799970068448035\", \"0.7751204321677446\", \"0.6945600252889785\", \"0.7768056304526473\"], \"12\": [\"0.125\", \"0.10523429421794395\", \"0.2118909125310025\", \"0.23489391114366323\", \"0.009646074369691601\", \"0.0\", \"0.11874761421371996\", \"0.0527955541221309\"], \"13\": [\"0.21621621621621623\", \"0.2755990793640338\", \"0.1969201674829802\", \"0.2953896409279389\", \"0.3015843931634597\", \"0.11554201048347584\", \"0.17548242292280566\", 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[\"0.9814230634419909\", \"0.9963978770381511\", \"1.0\", \"0.8218075211799654\", \"0.9591253663211922\", \"0.855653908628556\", \"1.0\", \"0.9731598153025469\"], \"21\": [\"0.4\", \"0.250038791297359\", \"0.40584941487144915\", \"0.3014925493939453\", \"0.572832617828055\", \"0.4124427574687024\", \"0.47851573961831473\", \"0.544650438336034\"], \"22\": [\"0.0784313725490196\", \"0.14995223132733781\", \"0.12311393437201215\", \"0.17565667327164983\", \"0.0\", \"0.131544112788465\", \"0.06008001069152505\", \"0.16566158911607187\"], \"23\": [\"0.13114754098360656\", \"0.15834272573578892\", \"0.03462685706967854\", \"0.0\", \"0.13399851975796426\", \"0.06428351916645836\", \"0.08231010130394614\", \"0.004070883213888515\"], \"24\": [\"0.8808204223873703\", \"0.848890252305633\", \"0.8638368844821835\", \"0.7660640805070529\", \"0.8965918083791469\", \"0.7883976569818673\", \"0.7281985649352972\", \"0.9923236715966286\"], \"25\": [\"0.9942279942279942\", \"0.7594144965282804\", 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Ethical Considerations

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[\"0.0\", \"0.16429095440635488\", \"0.0\", \"0.0\", \"0.0\", \"0.07168311553224681\", \"0.09235130658559526\", \"0.1310269931772118\", \"0.0\"], \"44\": [\"0.8717283072546229\", \"1.0\", \"0.8570517170387312\", \"0.8746594189789219\", \"0.8308022148127684\", \"0.8653946685389643\", \"0.7708804399994251\", \"0.8579005798224476\", \"0.7343811414228953\"], \"45\": [\"0.9814230634419909\", \"0.9963978770381511\", \"1.0\", \"0.8218075211799654\", \"0.9591253663211922\", \"0.855653908628556\", \"1.0\", \"0.9731598153025469\", \"0.876626125744864\"], \"46\": [\"0.4\", \"0.250038791297359\", \"0.40584941487144915\", \"0.3014925493939453\", \"0.572832617828055\", \"0.4124427574687024\", \"0.47851573961831473\", \"0.544650438336034\", \"0.5128191799957126\"], \"47\": [\"0.0784313725490196\", \"0.14995223132733781\", \"0.12311393437201215\", \"0.17565667327164983\", \"0.0\", \"0.131544112788465\", \"0.06008001069152505\", \"0.16566158911607187\", \"0.12769215042169926\"], \"48\": [\"0.13114754098360656\", \"0.15834272573578892\", \"0.03462685706967854\", \"0.0\", \"0.13399851975796426\", \"0.06428351916645836\", \"0.08231010130394614\", \"0.004070883213888515\", \"0.23011987591430827\"], \"49\": [\"0.8808204223873703\", \"0.848890252305633\", \"0.8638368844821835\", \"0.7660640805070529\", \"0.8965918083791469\", \"0.7883976569818673\", \"0.7281985649352972\", \"0.9923236715966286\", \"0.9134169503450666\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\", \"30\": \"0.7\", \"31\": \"0.7\", \"32\": \"0.7\", \"33\": \"0.7\", \"34\": \"0.7\", \"35\": \"0.7\", \"36\": \"0.7\", \"37\": \"0.7\", \"38\": \"0.7\", \"39\": \"0.7\", \"40\": \"0.7\", \"41\": \"0.7\", \"42\": \"0.7\", \"43\": \"0.7\", \"44\": \"0.7\", \"45\": \"0.7\", \"46\": \"0.7\", \"47\": \"0.7\", \"48\": \"0.7\", \"49\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"neutral\", \"2\": \"neutral\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"neutral\", \"6\": \"neutral\", \"7\": \"neutral\", \"8\": \"positive\", \"9\": \"positive\", \"10\": \"neutral\", \"11\": \"neutral\", \"12\": \"neutral\", \"13\": \"neutral\", \"14\": \"negative\", \"15\": \"negative\", \"16\": \"positive\", \"17\": \"neutral\", \"18\": \"neutral\", \"19\": \"neutral\", \"20\": \"neutral\", \"21\": \"neutral\", \"22\": \"neutral\", \"23\": \"neutral\", \"24\": \"neutral\", \"25\": \"neutral\", \"26\": \"neutral\", \"27\": \"neutral\", \"28\": \"neutral\", \"29\": \"neutral\", \"30\": \"neutral\", \"31\": \"neutral\", \"32\": \"neutral\", \"33\": \"positive\", \"34\": \"positive\", \"35\": \"neutral\", \"36\": \"neutral\", \"37\": \"neutral\", \"38\": \"positive\", \"39\": \"neutral\", \"40\": \"neutral\", \"41\": \"neutral\", \"42\": \"neutral\", \"43\": \"neutral\", \"44\": \"neutral\", \"45\": \"neutral\", \"46\": \"neutral\", \"47\": \"neutral\", \"48\": \"neutral\", \"49\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": false, \"5\": true, \"6\": false, \"7\": false, \"8\": false, \"9\": true, \"10\": true, \"11\": false, \"12\": false, \"13\": false, \"14\": true, \"15\": true, \"16\": false, \"17\": false, \"18\": false, \"19\": true, \"20\": true, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": true, \"26\": false, \"27\": false, \"28\": false, \"29\": true, \"30\": true, \"31\": false, \"32\": false, \"33\": false, \"34\": true, \"35\": true, \"36\": false, \"37\": false, \"38\": false, \"39\": true, \"40\": true, \"41\": false, \"42\": false, \"43\": false, \"44\": true, \"45\": true, \"46\": false, \"47\": false, \"48\": false, \"49\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"neutral\", \"2\": \"neutral\", \"3\": \"neutral\", \"4\": \"negative\", \"5\": \"negative\", \"6\": \"neutral\", \"7\": \"negative\", \"8\": \"positive\", \"9\": \"neutral\", \"10\": \"neutral\", \"11\": \"negative\", \"12\": \"negative\", \"13\": \"negative\", \"14\": \"neutral\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"neutral\", \"18\": \"neutral\", \"19\": \"negative\", \"20\": \"neutral\", \"21\": \"positive\", \"22\": \"neutral\", \"23\": \"negative\", \"24\": \"neutral\", \"25\": \"neutral\", \"26\": \"neutral\", \"27\": \"neutral\", \"28\": \"positive\", \"29\": \"negative\", \"30\": \"negative\", \"31\": \"positive\", \"32\": \"neutral\", \"33\": \"neutral\", \"34\": \"neutral\", \"35\": \"neutral\", \"36\": \"neutral\", \"37\": \"negative\", \"38\": \"negative\", \"39\": \"neutral\", \"40\": \"neutral\", \"41\": \"neutral\", \"42\": \"neutral\", \"43\": \"neutral\", \"44\": \"negative\", \"45\": \"neutral\", \"46\": \"positive\", \"47\": \"neutral\", \"48\": \"neutral\", \"49\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": false, \"5\": true, \"6\": false, \"7\": false, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": false, \"13\": false, \"14\": true, \"15\": true, \"16\": false, \"17\": false, \"18\": false, \"19\": true, \"20\": true, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": true, \"26\": false, \"27\": false, \"28\": false, \"29\": false, \"30\": true, \"31\": false, \"32\": false, \"33\": false, \"34\": true, \"35\": true, \"36\": true, \"37\": false, \"38\": false, \"39\": true, \"40\": true, \"41\": false, \"42\": false, \"43\": false, \"44\": true, \"45\": true, \"46\": false, \"47\": false, \"48\": false, \"49\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\", \"25\": \"Accuracy\", \"26\": \"Precision\", \"27\": \"Recall\", \"28\": \"F1 Score\", \"29\": \"AUROC\", \"30\": \"Accuracy\", \"31\": \"Precision\", \"32\": \"Recall\", \"33\": \"F1 Score\", \"34\": \"AUROC\", \"35\": \"Accuracy\", \"36\": \"Precision\", \"37\": \"Recall\", \"38\": \"F1 Score\", \"39\": \"AUROC\", \"40\": \"Accuracy\", \"41\": \"Precision\", \"42\": \"Recall\", \"43\": \"F1 Score\", \"44\": \"AUROC\", \"45\": \"Accuracy\", \"46\": \"Precision\", \"47\": \"Recall\", \"48\": \"F1 Score\", \"49\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"30\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"31\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"32\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"33\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"34\": [\"2021-09-01\", 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\"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"41\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"42\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"43\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"44\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"45\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"46\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"47\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"48\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"49\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"]}"); @@ -3260,10 +3263,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": 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\"39\": true, \"40\": true, \"41\": false, \"42\": false, \"43\": false, \"44\": true, \"45\": true, \"46\": false, \"47\": false, \"48\": false, \"49\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"neutral\", \"2\": \"neutral\", \"3\": \"neutral\", \"4\": \"negative\", \"5\": \"negative\", \"6\": \"neutral\", \"7\": \"negative\", \"8\": \"positive\", \"9\": \"neutral\", \"10\": \"neutral\", \"11\": \"negative\", \"12\": \"negative\", \"13\": \"negative\", \"14\": \"neutral\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"neutral\", \"18\": \"neutral\", \"19\": \"negative\", \"20\": \"neutral\", \"21\": \"positive\", \"22\": \"neutral\", \"23\": \"negative\", \"24\": \"neutral\", \"25\": \"neutral\", \"26\": \"neutral\", \"27\": \"neutral\", \"28\": \"positive\", \"29\": \"negative\", \"30\": \"negative\", \"31\": \"positive\", \"32\": \"neutral\", \"33\": \"neutral\", \"34\": \"neutral\", \"35\": \"neutral\", \"36\": \"neutral\", \"37\": \"negative\", \"38\": \"negative\", \"39\": \"neutral\", \"40\": \"neutral\", \"41\": \"neutral\", \"42\": \"neutral\", \"43\": \"neutral\", \"44\": \"negative\", \"45\": \"neutral\", \"46\": \"positive\", \"47\": \"neutral\", \"48\": \"neutral\", \"49\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": false, \"5\": true, \"6\": false, \"7\": false, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": false, \"13\": false, \"14\": true, \"15\": true, \"16\": false, \"17\": false, \"18\": false, \"19\": true, \"20\": true, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": true, \"26\": false, \"27\": false, \"28\": false, \"29\": false, \"30\": true, \"31\": false, \"32\": false, \"33\": false, \"34\": true, \"35\": true, \"36\": true, \"37\": false, \"38\": false, \"39\": true, \"40\": true, \"41\": false, \"42\": false, \"43\": false, \"44\": true, \"45\": true, \"46\": false, \"47\": false, \"48\": false, \"49\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\", \"25\": \"Accuracy\", \"26\": \"Precision\", \"27\": \"Recall\", \"28\": \"F1 Score\", \"29\": \"AUROC\", \"30\": \"Accuracy\", \"31\": \"Precision\", \"32\": \"Recall\", \"33\": \"F1 Score\", \"34\": \"AUROC\", \"35\": \"Accuracy\", \"36\": \"Precision\", \"37\": \"Recall\", \"38\": \"F1 Score\", \"39\": \"AUROC\", \"40\": \"Accuracy\", \"41\": \"Precision\", \"42\": \"Recall\", \"43\": \"F1 Score\", \"44\": \"AUROC\", \"45\": \"Accuracy\", \"46\": \"Precision\", \"47\": \"Recall\", \"48\": \"F1 Score\", \"49\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", 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[\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"48\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"], \"49\": [\"2021-09-01\", \"2021-10-01\", \"2021-10-01\", \"2021-11-01\", \"2021-11-01\", \"2021-12-01\", \"2021-12-01\", \"2022-01-01\", \"2022-01-01\"]}"); diff --git a/api/tutorials/nihcxr/cxr_classification.html b/api/tutorials/nihcxr/cxr_classification.html index f92e2041f..d511e162f 100644 --- a/api/tutorials/nihcxr/cxr_classification.html +++ b/api/tutorials/nihcxr/cxr_classification.html @@ -479,7 +479,7 @@

Import Libraries 
-/mnt/data/poetry/pycyclops-wIzUAwxh-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+/mnt/data/poetry/pycyclops-mhx6UJW0-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
   from .autonotebook import tqdm as notebook_tqdm

@@ -504,74 +504,74 @@

Generate Historical Reports 
-Flattening the indices: 100%|████████| 1000/1000 [00:55<00:00, 17.97 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 563220.63 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 237247.81 examples/s]
-Map: 100%|███████████████████████████| 400/400 [00:00<00:00, 1908.30 examples/s]
-Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 43377.76 examples/s]
-Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 43149.06 examples/s]
-Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45079.44 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 44577.57 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 45342.60 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 43014.09 example
+Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.71 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 550578.10 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 238096.28 examples/s]
+Map: 100%|███████████████████████████| 400/400 [00:00<00:00, 1893.89 examples/s]
+Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 43740.79 examples/s]
+Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 43260.32 examples/s]
+Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 44992.40 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 44819.32 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 45924.71 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 45090.35 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
-Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 46049.50 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.58 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 562163.79 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 241983.73 examples/s]
-Map: 100%|███████████████████████████| 396/396 [00:00<00:00, 1874.94 examples/s]
-Filter -> Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 40118.46 examples/s]
-Filter -> Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 34830.86 examples/s]
-Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 29268.26 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 24633.95 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 24704.67 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 26230.13 example
+Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45370.80 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.65 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 554215.64 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 238556.71 examples/s]
+Map: 100%|███████████████████████████| 396/396 [00:00<00:00, 1882.12 examples/s]
+Filter -> Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 43408.63 examples/s]
+Filter -> Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 42945.09 examples/s]
+Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 45858.37 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 44587.91 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 44751.30 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 16723.83 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
-Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 23274.26 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.20 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 563902.12 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 241593.46 examples/s]
-Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1791.06 examples/s]
-Filter -> Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 43233.27 examples/s]
-Filter -> Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 43037.52 examples/s]
-Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45409.84 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 24656.47 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 24065.83 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 26096.44 example
+Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 25961.99 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.21 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 544997.92 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 241065.81 examples/s]
+Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1794.05 examples/s]
+Filter -> Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 43309.03 examples/s]
+Filter -> Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42959.26 examples/s]
+Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45556.65 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 44647.54 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 45216.83 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 33329.57 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
-Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 22830.44 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:55<00:00, 17.97 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 553703.50 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 238910.00 examples/s]
-Map: 100%|███████████████████████████| 411/411 [00:00<00:00, 1892.96 examples/s]
-Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 44015.29 examples/s]
-Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 42956.86 examples/s]
-Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 46080.16 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 45419.69 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 45912.03 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 45787.64 example
+Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 46347.91 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.25 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 559389.70 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 239046.16 examples/s]
+Map: 100%|███████████████████████████| 411/411 [00:00<00:00, 1906.94 examples/s]
+Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 44019.79 examples/s]
+Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 44166.40 examples/s]
+Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 45872.93 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 44765.09 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 45796.16 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 45506.02 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
-Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47511.48 examples/s]
+Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47463.08 examples/s]

CyclOps offers a package for documentation of the model through a model report. The ModelCardReport class is used to populate and generate the model report as an HTML file. The model report has the following sections:

@@ -669,8 +669,8 @@

Model Creation 
-Filter: 100%|██████████| 1000/1000 [00:00<00:00, 157125.35 examples/s]
-Map: 100%|██████████| 661/661 [00:00<00:00, 1705.01 examples/s]
+Filter: 100%|██████████| 1000/1000 [00:00<00:00, 106190.29 examples/s]
+Map: 100%|██████████| 661/661 [00:00<00:00, 1674.04 examples/s]

@@ -797,9 +797,9 @@

Multilabel AUROC by Pathology and Sex 
-Filter -> Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 45324.92 examples/s]
-Filter -> Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 45879.97 examples/s]
-Filter -> overall: 100%|██████████| 661/661 [00:00<00:00, 47059.02 examples/s]
+Filter -> Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 46511.90 examples/s]
+Filter -> Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 42315.62 examples/s]
+Filter -> overall: 100%|██████████| 661/661 [00:00<00:00, 49624.74 examples/s]

@@ -860,16 +860,16 @@

Multilabel AUROC by Pathology and Age 
-Filter -> Patient Age:[19 - 35]: 100%|██████████| 661/661 [00:00<00:00, 43515.11 examples/s]
-Filter -> Patient Age:[35 - 65]: 100%|██████████| 661/661 [00:00<00:00, 47717.51 examples/s]
-Filter -> Patient Age:[65 - 100]: 100%|██████████| 661/661 [00:00<00:00, 47175.93 examples/s]
-Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 46420.01 examples/s]
-Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 45975.84 examples/s]
-Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 44598.72 examples/s]
-Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 40254.31 examples/s]
-Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 44062.86 examples/s]
-Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 46133.44 examples/s]
-Filter -> overall: 100%|██████████| 661/661 [00:00<00:00, 46033.09 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|██████████| 661/661 [00:00<00:00, 46425.45 examples/s]
+Filter -> Patient Age:[35 - 65]: 100%|██████████| 661/661 [00:00<00:00, 48688.75 examples/s]
+Filter -> Patient Age:[65 - 100]: 100%|██████████| 661/661 [00:00<00:00, 45820.83 examples/s]
+Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 45602.26 examples/s]
+Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 48722.98 examples/s]
+Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 44049.56 examples/s]
+Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 44852.70 examples/s]
+Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|██████████| 661/661 [00:00<00:00, 44538.54 examples/s]
+Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|██████████| 661/661 [00:00<00:00, 44315.00 examples/s]
+Filter -> overall: 100%|██████████| 661/661 [00:00<00:00, 44226.63 examples/s]

@@ -926,9 +926,9 @@

Multilabel AUROC by Pathology and Age

-
+
@@ -6615,7 +6615,7 @@

Graphics

-
+
@@ -6623,7 +6623,7 @@

Graphics

-
+
@@ -8210,6 +8210,9 @@

Quantitative Analysis

+ + + diff --git a/api/tutorials/synthea/length_of_stay_report_periodic.html b/api/tutorials/synthea/length_of_stay_report_periodic.html index 66d0372a8..4ce0c4aa0 100644 --- a/api/tutorials/synthea/length_of_stay_report_periodic.html +++ b/api/tutorials/synthea/length_of_stay_report_periodic.html @@ -647,7 +647,7 @@

A quick glance of your most import
- 0.75 + 0.79 @@ -680,7 +680,7 @@

A quick glance of your most import
- 0.73 + 1.0 @@ -713,7 +713,7 @@

A quick glance of your most import
- 0.89 + 1.0 @@ -746,7 +746,7 @@

A quick glance of your most import
- 0.76 + 0.99 @@ -779,7 +779,7 @@

A quick glance of your most import
- 0.99 + 0.93 @@ -1044,7 +1044,7 @@

Graphics

-
+
@@ -1052,7 +1052,7 @@

Graphics

-
+
@@ -1060,7 +1060,7 @@

Graphics

-
+
@@ -1068,7 +1068,7 @@

Graphics

-
+
@@ -1076,7 +1076,7 @@

Graphics

-
+
@@ -1157,7 +1157,7 @@

Quantitative Analysis
- 0.75 + 0.79 @@ -1190,7 +1190,7 @@

Quantitative Analysis
- 0.73 + 1.0 @@ -1223,7 +1223,7 @@

Quantitative Analysis
- 0.89 + 1.0 @@ -1256,7 +1256,7 @@

Quantitative Analysis
- 0.76 + 0.99 @@ -1289,7 +1289,7 @@

Quantitative Analysis
- 0.99 + 0.93 @@ -1307,6 +1307,9 @@

Quantitative Analysis

+ + +
@@ -1347,7 +1350,7 @@

Graphics

-
+
@@ -1355,7 +1358,7 @@

Graphics

-
+
@@ -1410,7 +1413,7 @@

Version

- Date: 2023-11-23 + Date: 2023-11-24
@@ -1628,26 +1631,22 @@

Model Parameters

-

Objective

- binary:logistic +

Colsample_bytree

+ 1
-
-

Seed

- 123 -
-

Colsample_bytree

- 0.7 +

Eval_metric

+ logloss
@@ -1674,6 +1673,10 @@

Colsample_bytree

+
+

Learning_rate

+ 0.1 +
@@ -1689,15 +1692,15 @@

Colsample_bytree

-
-

Min_child_weight

- 3 -
+
+

Objective

+ binary:logistic +
@@ -1723,10 +1726,6 @@

Min_child_weight

-
-

Missing

- nan -
@@ -1742,6 +1741,10 @@

Missing

+
+

Enable_categorical

+ False +
@@ -1752,10 +1755,6 @@

Missing

-
-

Random_state

- 123 -
@@ -1766,32 +1765,28 @@

Random_state

-
-

Reg_lambda

- 1 -
+
+

Gamma

+ 2 +
-
-

Learning_rate

- 0.1 -
-

Eval_metric

- logloss +

N_estimators

+ 500
@@ -1799,8 +1794,8 @@

Eval_metric

-

Enable_categorical

- False +

Missing

+ nan
@@ -1812,21 +1807,37 @@

Enable_categorical

+
+

Max_depth

+ 2 +
+
+

Reg_lambda

+ 0 +
+
+

Random_state

+ 123 +
+
+

Seed

+ 123 +
@@ -1842,33 +1853,25 @@

Enable_categorical

+
+

Min_child_weight

+ 3 +
-
-

Max_depth

- 5 -
-
-

N_estimators

- 100 -
-
-

Gamma

- 1 -
@@ -2149,7 +2152,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [20, 21, 22, 23, 24] - var histories = JSON.parse("{\"0\": [\"0.8823529411764706\", \"0.9047459027620671\", \"0.916305532289785\", \"0.9744122224824191\", \"0.7099534380591017\"], \"1\": [\"0.9090909090909091\", \"0.9578826853548222\", \"0.917374373709721\", \"0.9935463578246547\", \"0.8601500527924701\"], \"2\": [\"0.8823529411764706\", \"0.849704784323048\", \"0.9069849579184136\", \"0.9430290974291198\", \"0.8747524428595284\"], \"3\": [\"0.8955223880597015\", \"0.8734495355215972\", \"0.8407668445158849\", \"0.9256490683644405\", \"0.8216610485442066\"], \"4\": [\"0.9622260668973472\", \"0.8186739139024191\", \"0.8124847960494955\", \"0.9064256281141911\", \"0.833413199011447\"], \"5\": [\"0.8571428571428571\", \"0.5819201870139827\", \"0.9130841782663768\", \"0.8841536976452296\", \"0.7985708804530586\"], \"6\": [\"0.9090909090909091\", \"0.8671151748438145\", \"0.9487979641579005\", \"0.9803598302713871\", \"0.8803234648791339\"], \"7\": [\"0.8\", \"0.8143811156649716\", \"0.815614403139397\", \"0.771192489887751\", \"0.9571144943417136\"], \"8\": [\"0.851063829787234\", \"0.92127216573453\", \"0.7184008545433266\", \"0.8766415524925694\", \"0.758252155680523\"], \"9\": [\"0.96\", \"0.9911055456871667\", \"0.9080444777732023\", \"0.8164564307743034\", \"0.9236907602104834\"], \"10\": [\"0.9032258064516129\", \"0.89246084600083\", \"1.0\", \"0.900458486250579\", \"0.940962004062729\"], \"11\": [\"0.9375\", \"0.9761126475691007\", \"0.7820641878550596\", \"0.787032935786996\", \"0.7148288213945461\"], \"12\": [\"0.9146341463414634\", \"0.8902223738196369\", \"0.9281285384261461\", \"0.8533661618221544\", \"0.7343936243028254\"], \"13\": [\"0.9259259259259259\", \"0.9886559698482303\", \"0.9207212879568217\", \"0.8085778091382767\", \"0.8951957117061097\"], \"14\": [\"0.9670441347270615\", \"1.0\", \"0.991838934499501\", \"0.9908136397161763\", \"0.8310871264631631\"], \"15\": [\"0.9117647058823529\", \"0.8790126246355432\", \"0.9092082611628853\", \"0.8460654049212386\", \"0.9496091296957796\"], \"16\": [\"0.95\", \"0.9232635939052443\", \"0.9425100078531611\", \"0.9277021061192503\", \"1.0\"], \"17\": [\"0.9047619047619048\", \"0.9027908731566985\", \"1.0\", \"0.8875348246503013\", \"0.8069385919384355\"], \"18\": [\"0.926829268292683\", \"0.9522266490735485\", \"0.9018104132942503\", \"0.7915252539097856\", \"0.9359074480535754\"], \"19\": [\"0.981074481074481\", \"1.0\", \"0.7819585586196038\", \"1.0\", \"0.8789063987631572\"], \"20\": [\"0.9070796460176991\", \"0.8997174316885451\", \"0.9292880188957555\", \"0.7636603313250567\", \"0.7457429916634252\"], \"21\": [\"0.9428571428571428\", \"1.0\", \"1.0\", \"0.8947250627918201\", \"0.733492840646206\"], \"22\": [\"0.9103448275862069\", \"0.7232864022605469\", \"0.8044994643551593\", \"0.9692929367096494\", \"0.8899407878997421\"], \"23\": [\"0.9263157894736842\", \"0.8347500429991865\", \"0.986411266387445\", \"0.9711075162543921\", \"0.764271736289223\"], \"24\": [\"0.9721583652618137\", \"1.0\", \"1.0\", \"0.9226879759060611\", \"0.9900931412061483\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8407079646017699\", \"0.90643061238161\", \"0.832538414243798\", \"1.0\", \"0.7903377238829272\"], \"1\": [\"1.0\", \"0.998798894332237\", \"0.8049446014157483\", \"0.9442388518379021\", \"1.0\"], \"2\": [\"0.7391304347826086\", \"0.5555228850199307\", \"0.8628022522718521\", \"0.6852707406087278\", \"0.5911338791069285\"], \"3\": [\"0.85\", \"0.8131678365712649\", \"0.8371538920381149\", \"0.7292041942131848\", \"0.9276223876257275\"], \"4\": [\"0.9632740447957839\", \"1.0\", \"0.8740769658302125\", \"1.0\", \"1.0\"], \"5\": [\"0.7962962962962963\", \"0.9709600245667258\", \"0.9540250492115908\", \"0.9257146674107212\", \"0.7500485707771797\"], \"6\": [\"0.85\", \"0.9519549119718769\", \"0.8116268947042299\", \"0.8263715452846059\", \"0.7685932252575909\"], \"7\": [\"0.68\", \"0.9361178100833059\", \"0.7417276185558737\", \"0.6278658347131162\", \"0.8093914275322115\"], \"8\": [\"0.7555555555555555\", \"0.8733797829085564\", \"0.9139777724427962\", \"0.7274359219329875\", \"0.816763287022757\"], \"9\": [\"0.9006896551724138\", \"0.8270078496339749\", \"1.0\", \"0.9766227712699306\", \"0.8525986727361025\"], \"10\": [\"0.8455284552845529\", \"0.6938732202384621\", \"1.0\", \"0.9229630849776538\", \"0.9578601703160796\"], \"11\": [\"1.0\", \"0.9341400304893195\", \"0.9745721659711388\", \"1.0\", \"1.0\"], \"12\": [\"0.7738095238095238\", \"0.6663789680469527\", \"0.7159299436442419\", \"0.8001685572531141\", \"0.8326055839996588\"], \"13\": [\"0.87248322147651\", \"0.8813537104577479\", \"0.9012245322673739\", \"1.0\", \"0.7822916793780839\"], \"14\": [\"0.9490231990231991\", \"0.9782604481330335\", \"0.9029707492428839\", \"0.8616772330685437\", \"0.8431521928923481\"], \"15\": [\"0.8640776699029126\", \"0.6486536852663003\", \"0.9681695036372805\", \"1.0\", \"0.846995183504722\"], \"16\": [\"0.9272727272727272\", \"0.9172841435537059\", \"0.9445102491870424\", \"0.8927320622600079\", \"0.9288038891432359\"], \"17\": [\"0.8360655737704918\", \"0.8824035993958579\", \"0.8784029349996647\", \"0.8890907385219458\", \"1.0\"], \"18\": [\"0.8793103448275862\", \"0.7065211059090846\", \"0.9055079225441419\", \"0.9091827169398103\", \"1.0\"], \"19\": [\"0.9644808743169399\", \"0.8668884259518921\", \"1.0\", \"0.8331697890399169\", \"1.0\"], \"20\": [\"0.8539823008849557\", \"1.0\", \"0.8209700904304302\", \"0.8244875386670434\", \"0.7860923361290615\"], \"21\": [\"0.9666666666666667\", \"1.0\", \"0.9306278916430111\", \"1.0\", \"1.0\"], \"22\": [\"0.8\", \"0.9336344082039157\", \"0.6839647635975962\", \"0.8435301342641975\", \"1.0\"], \"23\": [\"0.8754716981132076\", \"0.8952672498140729\", \"0.8181157462099988\", \"1.0\", \"0.9898128443728897\"], \"24\": [\"0.95436355896126\", \"1.0\", \"1.0\", \"0.9797659960250391\", \"0.9297513701430263\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2430,10 +2433,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8823529411764706\", \"0.9047459027620671\", \"0.916305532289785\", \"0.9744122224824191\", \"0.7099534380591017\"], \"1\": [\"0.9090909090909091\", \"0.9578826853548222\", \"0.917374373709721\", \"0.9935463578246547\", \"0.8601500527924701\"], \"2\": [\"0.8823529411764706\", \"0.849704784323048\", \"0.9069849579184136\", \"0.9430290974291198\", \"0.8747524428595284\"], \"3\": [\"0.8955223880597015\", \"0.8734495355215972\", \"0.8407668445158849\", \"0.9256490683644405\", \"0.8216610485442066\"], \"4\": [\"0.9622260668973472\", \"0.8186739139024191\", \"0.8124847960494955\", \"0.9064256281141911\", \"0.833413199011447\"], \"5\": [\"0.8571428571428571\", \"0.5819201870139827\", \"0.9130841782663768\", \"0.8841536976452296\", \"0.7985708804530586\"], \"6\": [\"0.9090909090909091\", \"0.8671151748438145\", \"0.9487979641579005\", \"0.9803598302713871\", \"0.8803234648791339\"], \"7\": [\"0.8\", \"0.8143811156649716\", \"0.815614403139397\", \"0.771192489887751\", \"0.9571144943417136\"], \"8\": [\"0.851063829787234\", \"0.92127216573453\", \"0.7184008545433266\", \"0.8766415524925694\", \"0.758252155680523\"], \"9\": [\"0.96\", \"0.9911055456871667\", \"0.9080444777732023\", \"0.8164564307743034\", \"0.9236907602104834\"], \"10\": [\"0.9032258064516129\", \"0.89246084600083\", \"1.0\", \"0.900458486250579\", \"0.940962004062729\"], \"11\": [\"0.9375\", \"0.9761126475691007\", \"0.7820641878550596\", \"0.787032935786996\", \"0.7148288213945461\"], \"12\": [\"0.9146341463414634\", \"0.8902223738196369\", \"0.9281285384261461\", \"0.8533661618221544\", \"0.7343936243028254\"], \"13\": [\"0.9259259259259259\", \"0.9886559698482303\", \"0.9207212879568217\", \"0.8085778091382767\", \"0.8951957117061097\"], \"14\": [\"0.9670441347270615\", \"1.0\", \"0.991838934499501\", \"0.9908136397161763\", \"0.8310871264631631\"], \"15\": [\"0.9117647058823529\", \"0.8790126246355432\", \"0.9092082611628853\", \"0.8460654049212386\", \"0.9496091296957796\"], \"16\": [\"0.95\", \"0.9232635939052443\", \"0.9425100078531611\", \"0.9277021061192503\", \"1.0\"], \"17\": [\"0.9047619047619048\", \"0.9027908731566985\", \"1.0\", \"0.8875348246503013\", \"0.8069385919384355\"], \"18\": [\"0.926829268292683\", \"0.9522266490735485\", \"0.9018104132942503\", \"0.7915252539097856\", \"0.9359074480535754\"], \"19\": [\"0.981074481074481\", \"1.0\", \"0.7819585586196038\", \"1.0\", \"0.8789063987631572\"], \"20\": [\"0.9070796460176991\", \"0.8997174316885451\", \"0.9292880188957555\", \"0.7636603313250567\", \"0.7457429916634252\"], \"21\": [\"0.9428571428571428\", \"1.0\", \"1.0\", \"0.8947250627918201\", \"0.733492840646206\"], \"22\": [\"0.9103448275862069\", \"0.7232864022605469\", \"0.8044994643551593\", \"0.9692929367096494\", \"0.8899407878997421\"], \"23\": [\"0.9263157894736842\", \"0.8347500429991865\", \"0.986411266387445\", \"0.9711075162543921\", \"0.764271736289223\"], \"24\": [\"0.9721583652618137\", \"1.0\", \"1.0\", \"0.9226879759060611\", \"0.9900931412061483\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8407079646017699\", \"0.90643061238161\", \"0.832538414243798\", \"1.0\", \"0.7903377238829272\"], \"1\": [\"1.0\", \"0.998798894332237\", \"0.8049446014157483\", \"0.9442388518379021\", \"1.0\"], \"2\": [\"0.7391304347826086\", \"0.5555228850199307\", \"0.8628022522718521\", \"0.6852707406087278\", \"0.5911338791069285\"], \"3\": [\"0.85\", \"0.8131678365712649\", \"0.8371538920381149\", \"0.7292041942131848\", \"0.9276223876257275\"], \"4\": [\"0.9632740447957839\", \"1.0\", \"0.8740769658302125\", \"1.0\", \"1.0\"], \"5\": [\"0.7962962962962963\", \"0.9709600245667258\", \"0.9540250492115908\", \"0.9257146674107212\", \"0.7500485707771797\"], \"6\": [\"0.85\", \"0.9519549119718769\", \"0.8116268947042299\", \"0.8263715452846059\", \"0.7685932252575909\"], \"7\": [\"0.68\", \"0.9361178100833059\", \"0.7417276185558737\", \"0.6278658347131162\", \"0.8093914275322115\"], \"8\": [\"0.7555555555555555\", \"0.8733797829085564\", \"0.9139777724427962\", \"0.7274359219329875\", \"0.816763287022757\"], \"9\": [\"0.9006896551724138\", \"0.8270078496339749\", \"1.0\", \"0.9766227712699306\", \"0.8525986727361025\"], \"10\": [\"0.8455284552845529\", \"0.6938732202384621\", \"1.0\", \"0.9229630849776538\", \"0.9578601703160796\"], \"11\": [\"1.0\", \"0.9341400304893195\", \"0.9745721659711388\", \"1.0\", \"1.0\"], \"12\": [\"0.7738095238095238\", \"0.6663789680469527\", \"0.7159299436442419\", \"0.8001685572531141\", \"0.8326055839996588\"], \"13\": [\"0.87248322147651\", \"0.8813537104577479\", \"0.9012245322673739\", \"1.0\", \"0.7822916793780839\"], \"14\": [\"0.9490231990231991\", \"0.9782604481330335\", \"0.9029707492428839\", \"0.8616772330685437\", \"0.8431521928923481\"], \"15\": [\"0.8640776699029126\", \"0.6486536852663003\", \"0.9681695036372805\", \"1.0\", \"0.846995183504722\"], \"16\": [\"0.9272727272727272\", \"0.9172841435537059\", \"0.9445102491870424\", \"0.8927320622600079\", \"0.9288038891432359\"], \"17\": [\"0.8360655737704918\", \"0.8824035993958579\", \"0.8784029349996647\", \"0.8890907385219458\", \"1.0\"], \"18\": [\"0.8793103448275862\", \"0.7065211059090846\", \"0.9055079225441419\", \"0.9091827169398103\", \"1.0\"], \"19\": [\"0.9644808743169399\", \"0.8668884259518921\", \"1.0\", \"0.8331697890399169\", \"1.0\"], \"20\": [\"0.8539823008849557\", \"1.0\", \"0.8209700904304302\", \"0.8244875386670434\", \"0.7860923361290615\"], \"21\": [\"0.9666666666666667\", \"1.0\", \"0.9306278916430111\", \"1.0\", \"1.0\"], \"22\": [\"0.8\", \"0.9336344082039157\", \"0.6839647635975962\", \"0.8435301342641975\", \"1.0\"], \"23\": [\"0.8754716981132076\", \"0.8952672498140729\", \"0.8181157462099988\", \"1.0\", \"0.9898128443728897\"], \"24\": [\"0.95436355896126\", \"1.0\", \"1.0\", \"0.9797659960250391\", \"0.9297513701430263\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"neutral\", \"2\": \"neutral\", \"3\": \"neutral\", \"4\": \"negative\", \"5\": \"positive\", \"6\": \"neutral\", \"7\": \"positive\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"neutral\", \"11\": \"negative\", \"12\": \"negative\", \"13\": \"negative\", \"14\": \"negative\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"negative\", \"19\": \"negative\", \"20\": \"negative\", \"21\": \"negative\", \"22\": \"positive\", \"23\": \"negative\", \"24\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"neutral\", \"2\": \"negative\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"neutral\", \"8\": \"neutral\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"neutral\", \"12\": \"positive\", \"13\": \"neutral\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"positive\", \"19\": \"neutral\", \"20\": \"negative\", \"21\": \"neutral\", \"22\": \"positive\", \"23\": \"positive\", \"24\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2706,10 +2709,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8823529411764706\", \"0.9047459027620671\", \"0.916305532289785\", \"0.9744122224824191\", \"0.7099534380591017\"], \"1\": [\"0.9090909090909091\", \"0.9578826853548222\", \"0.917374373709721\", \"0.9935463578246547\", \"0.8601500527924701\"], \"2\": [\"0.8823529411764706\", \"0.849704784323048\", \"0.9069849579184136\", \"0.9430290974291198\", \"0.8747524428595284\"], \"3\": [\"0.8955223880597015\", \"0.8734495355215972\", \"0.8407668445158849\", \"0.9256490683644405\", \"0.8216610485442066\"], \"4\": [\"0.9622260668973472\", \"0.8186739139024191\", \"0.8124847960494955\", \"0.9064256281141911\", \"0.833413199011447\"], \"5\": [\"0.8571428571428571\", \"0.5819201870139827\", \"0.9130841782663768\", \"0.8841536976452296\", \"0.7985708804530586\"], \"6\": [\"0.9090909090909091\", \"0.8671151748438145\", \"0.9487979641579005\", \"0.9803598302713871\", \"0.8803234648791339\"], \"7\": [\"0.8\", \"0.8143811156649716\", \"0.815614403139397\", \"0.771192489887751\", \"0.9571144943417136\"], \"8\": [\"0.851063829787234\", \"0.92127216573453\", \"0.7184008545433266\", \"0.8766415524925694\", \"0.758252155680523\"], \"9\": [\"0.96\", \"0.9911055456871667\", \"0.9080444777732023\", \"0.8164564307743034\", \"0.9236907602104834\"], \"10\": [\"0.9032258064516129\", \"0.89246084600083\", \"1.0\", \"0.900458486250579\", \"0.940962004062729\"], \"11\": [\"0.9375\", \"0.9761126475691007\", \"0.7820641878550596\", \"0.787032935786996\", \"0.7148288213945461\"], \"12\": [\"0.9146341463414634\", \"0.8902223738196369\", \"0.9281285384261461\", \"0.8533661618221544\", \"0.7343936243028254\"], \"13\": [\"0.9259259259259259\", \"0.9886559698482303\", \"0.9207212879568217\", \"0.8085778091382767\", \"0.8951957117061097\"], \"14\": [\"0.9670441347270615\", \"1.0\", \"0.991838934499501\", \"0.9908136397161763\", \"0.8310871264631631\"], \"15\": [\"0.9117647058823529\", \"0.8790126246355432\", \"0.9092082611628853\", \"0.8460654049212386\", \"0.9496091296957796\"], \"16\": [\"0.95\", \"0.9232635939052443\", \"0.9425100078531611\", \"0.9277021061192503\", \"1.0\"], \"17\": [\"0.9047619047619048\", \"0.9027908731566985\", \"1.0\", \"0.8875348246503013\", \"0.8069385919384355\"], \"18\": [\"0.926829268292683\", \"0.9522266490735485\", \"0.9018104132942503\", \"0.7915252539097856\", \"0.9359074480535754\"], \"19\": [\"0.981074481074481\", \"1.0\", \"0.7819585586196038\", \"1.0\", \"0.8789063987631572\"], \"20\": [\"0.9070796460176991\", \"0.8997174316885451\", \"0.9292880188957555\", \"0.7636603313250567\", \"0.7457429916634252\"], \"21\": [\"0.9428571428571428\", \"1.0\", \"1.0\", \"0.8947250627918201\", \"0.733492840646206\"], \"22\": [\"0.9103448275862069\", \"0.7232864022605469\", \"0.8044994643551593\", \"0.9692929367096494\", \"0.8899407878997421\"], \"23\": [\"0.9263157894736842\", \"0.8347500429991865\", \"0.986411266387445\", \"0.9711075162543921\", \"0.764271736289223\"], \"24\": [\"0.9721583652618137\", \"1.0\", \"1.0\", \"0.9226879759060611\", \"0.9900931412061483\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8407079646017699\", \"0.90643061238161\", \"0.832538414243798\", \"1.0\", \"0.7903377238829272\"], \"1\": [\"1.0\", \"0.998798894332237\", \"0.8049446014157483\", \"0.9442388518379021\", \"1.0\"], \"2\": [\"0.7391304347826086\", \"0.5555228850199307\", \"0.8628022522718521\", \"0.6852707406087278\", \"0.5911338791069285\"], \"3\": [\"0.85\", \"0.8131678365712649\", \"0.8371538920381149\", \"0.7292041942131848\", \"0.9276223876257275\"], \"4\": [\"0.9632740447957839\", \"1.0\", \"0.8740769658302125\", \"1.0\", \"1.0\"], \"5\": [\"0.7962962962962963\", \"0.9709600245667258\", \"0.9540250492115908\", \"0.9257146674107212\", \"0.7500485707771797\"], \"6\": [\"0.85\", \"0.9519549119718769\", \"0.8116268947042299\", \"0.8263715452846059\", \"0.7685932252575909\"], \"7\": [\"0.68\", \"0.9361178100833059\", \"0.7417276185558737\", \"0.6278658347131162\", \"0.8093914275322115\"], \"8\": [\"0.7555555555555555\", \"0.8733797829085564\", \"0.9139777724427962\", \"0.7274359219329875\", \"0.816763287022757\"], \"9\": [\"0.9006896551724138\", \"0.8270078496339749\", \"1.0\", \"0.9766227712699306\", \"0.8525986727361025\"], \"10\": [\"0.8455284552845529\", \"0.6938732202384621\", \"1.0\", \"0.9229630849776538\", \"0.9578601703160796\"], \"11\": [\"1.0\", \"0.9341400304893195\", \"0.9745721659711388\", \"1.0\", \"1.0\"], \"12\": [\"0.7738095238095238\", \"0.6663789680469527\", \"0.7159299436442419\", \"0.8001685572531141\", \"0.8326055839996588\"], \"13\": [\"0.87248322147651\", \"0.8813537104577479\", \"0.9012245322673739\", \"1.0\", \"0.7822916793780839\"], \"14\": [\"0.9490231990231991\", \"0.9782604481330335\", \"0.9029707492428839\", \"0.8616772330685437\", \"0.8431521928923481\"], \"15\": [\"0.8640776699029126\", \"0.6486536852663003\", \"0.9681695036372805\", \"1.0\", \"0.846995183504722\"], \"16\": [\"0.9272727272727272\", \"0.9172841435537059\", \"0.9445102491870424\", \"0.8927320622600079\", \"0.9288038891432359\"], \"17\": [\"0.8360655737704918\", \"0.8824035993958579\", \"0.8784029349996647\", \"0.8890907385219458\", \"1.0\"], \"18\": [\"0.8793103448275862\", \"0.7065211059090846\", \"0.9055079225441419\", \"0.9091827169398103\", \"1.0\"], \"19\": [\"0.9644808743169399\", \"0.8668884259518921\", \"1.0\", \"0.8331697890399169\", \"1.0\"], \"20\": [\"0.8539823008849557\", \"1.0\", \"0.8209700904304302\", \"0.8244875386670434\", \"0.7860923361290615\"], \"21\": [\"0.9666666666666667\", \"1.0\", \"0.9306278916430111\", \"1.0\", \"1.0\"], \"22\": [\"0.8\", \"0.9336344082039157\", \"0.6839647635975962\", \"0.8435301342641975\", \"1.0\"], \"23\": [\"0.8754716981132076\", \"0.8952672498140729\", \"0.8181157462099988\", \"1.0\", \"0.9898128443728897\"], \"24\": [\"0.95436355896126\", \"1.0\", \"1.0\", \"0.9797659960250391\", \"0.9297513701430263\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"neutral\", \"2\": \"neutral\", \"3\": \"neutral\", \"4\": \"negative\", \"5\": \"positive\", \"6\": \"neutral\", \"7\": \"positive\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"neutral\", \"11\": \"negative\", \"12\": \"negative\", \"13\": \"negative\", \"14\": \"negative\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"negative\", \"19\": \"negative\", \"20\": \"negative\", \"21\": \"negative\", \"22\": \"positive\", \"23\": \"negative\", \"24\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"neutral\", \"2\": \"negative\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"neutral\", \"8\": \"neutral\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"neutral\", \"12\": \"positive\", \"13\": \"neutral\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"positive\", \"19\": \"neutral\", \"20\": \"negative\", \"21\": \"neutral\", \"22\": \"positive\", \"23\": \"positive\", \"24\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); diff --git a/api/tutorials/synthea/los_prediction.html b/api/tutorials/synthea/los_prediction.html index b5c33c507..abe4fecc0 100644 --- a/api/tutorials/synthea/los_prediction.html +++ b/api/tutorials/synthea/los_prediction.html @@ -490,7 +490,7 @@

Import Libraries 
-/mnt/data/poetry/pycyclops-wIzUAwxh-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+/mnt/data/poetry/pycyclops-mhx6UJW0-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
   from .autonotebook import tqdm as notebook_tqdm

@@ -685,17 +685,17 @@

Compute length of stay (labels) 
-2023-11-23 08:34:13,665 INFO cycquery.orm    - Database setup, ready to run queries!
-2023-11-23 08:34:18,616 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:34:18,617 INFO cycquery.utils.profile - Finished executing function run_query in 3.687719 s
-2023-11-23 08:34:20,410 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:34:20,412 INFO cycquery.utils.profile - Finished executing function run_query in 1.793909 s
-2023-11-23 08:34:21,652 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:34:21,653 INFO cycquery.utils.profile - Finished executing function run_query in 0.393491 s
-2023-11-23 08:34:22,156 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:34:22,157 INFO cycquery.utils.profile - Finished executing function run_query in 0.499417 s
-2023-11-23 08:34:22,246 INFO cycquery.orm    - Query returned successfully!
-2023-11-23 08:34:22,248 INFO cycquery.utils.profile - Finished executing function run_query in 0.089593 s
+2023-11-24 11:22:21,628 INFO cycquery.orm    - Database setup, ready to run queries!
+2023-11-24 11:22:26,635 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:22:26,636 INFO cycquery.utils.profile - Finished executing function run_query in 3.683744 s
+2023-11-24 11:22:28,424 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:22:28,425 INFO cycquery.utils.profile - Finished executing function run_query in 1.788084 s
+2023-11-24 11:22:29,673 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:22:29,675 INFO cycquery.utils.profile - Finished executing function run_query in 0.392405 s
+2023-11-24 11:22:30,177 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:22:30,179 INFO cycquery.utils.profile - Finished executing function run_query in 0.499542 s
+2023-11-24 11:22:30,271 INFO cycquery.orm    - Query returned successfully!
+2023-11-24 11:22:30,272 INFO cycquery.utils.profile - Finished executing function run_query in 0.092379 s

@@ -748,9 +748,9 @@

Drop NaNs based on the

-
- + +

Archive

Archive

2023​

diff --git a/blog/cyclops-alpha-release/index.html b/blog/cyclops-alpha-release/index.html index b9b80cfad..a96a88116 100644 --- a/blog/cyclops-alpha-release/index.html +++ b/blog/cyclops-alpha-release/index.html @@ -5,8 +5,8 @@ CyclOps Alpha Release | CyclOps - - + +

CyclOps Alpha Release

· One min read
Amrit Krishnan

Developing machine learning (ML) systems for clinical use cases is difficult. Furthermore, evaluating ML models diff --git a/blog/index.html b/blog/index.html index c65d968be..d9409d6eb 100644 --- a/blog/index.html +++ b/blog/index.html @@ -5,8 +5,8 @@ Blog | CyclOps - - + +

· One min read
Amrit Krishnan

Developing machine learning (ML) systems for clinical use cases is difficult. Furthermore, evaluating ML models diff --git a/blog/tags/alpha/index.html b/blog/tags/alpha/index.html index 734449f87..19611f588 100644 --- a/blog/tags/alpha/index.html +++ b/blog/tags/alpha/index.html @@ -5,8 +5,8 @@ One post tagged with "alpha" | CyclOps - - + +

One post tagged with "alpha"

View All Tags

· One min read
Amrit Krishnan

Developing machine learning (ML) systems for clinical use cases is difficult. Furthermore, evaluating ML models diff --git a/blog/tags/index.html b/blog/tags/index.html index 1d3ecb26e..7c1f732e6 100644 --- a/blog/tags/index.html +++ b/blog/tags/index.html @@ -5,8 +5,8 @@ Tags | CyclOps - - + +

Tags

diff --git a/docs/intro/index.html b/docs/intro/index.html index 882502cb0..0858bed17 100644 --- a/docs/intro/index.html +++ b/docs/intro/index.html @@ -5,8 +5,8 @@ intro | CyclOps - - + +

intro

Getting Started​

diff --git a/index.html b/index.html index fc871b86d..de8749247 100644 --- a/index.html +++ b/index.html @@ -5,8 +5,8 @@ CyclOps | CyclOps - - + +

CyclOps

Cyclical development towards Operationalizing ML models for healthcare

Rigorous Evaluation

CyclOps APIs support rigorous evaluation across patient sub-populations

Deployment and Operationalization

By leveraging powerful open source tools, CyclOps provides a modular and extensible MLOps platform for healthcare

Monitoring

CyclOps supports monitoring of clinical ML models for dataset shifts

diff --git a/markdown-page/index.html b/markdown-page/index.html index 51d826a6c..49cefc183 100644 --- a/markdown-page/index.html +++ b/markdown-page/index.html @@ -5,8 +5,8 @@ Markdown page example | CyclOps - - + +

Markdown page example