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Machine Learning to Enhance Detection of Diagnostic Safety Events

Contents overview current as of 2022-04-28, commit id b066d83.

  • root
    • ICD code groupers (dizzy, headache, stroke-risk, stroke)
    • medication groupers
  • AIM2/
    • "Original" classifier ipynb? Applies sklearn to SPADE data.
    • Some old scripts to generate fake data.
    • Mostly from late 2020.
  • AndyZimolzak/
    • ipynb, SQL, and RPT files serving as an intro to structured data
    • SQL and TXT files related to note titles (AMA, discharge, and in general)
    • slightly modified classifier.ipynb
    • TXT file listing conda packages
    • python helper functions and tests
    • Graphviz file of PERT diagram of onboarding
    • ipynb to inspect a few UMAP'd discharge summaries from Max
    • LaTeX notation about discharge summary embeddings
  • Justin/
    • The things we use the most are in the Stroke_Notes_13OCT21 folder.
    • cui semi-manual filtering ipynb
    • word2vec ipynb (pytorch)
    • UMAP "octopus" 1Hot ipynb
    • UMAP "whale" CUIDocumentVectors.ipynb
    • CSV of discharge summ note titles, adjudicated by Andy
    • TXTs of 140 note types, 90 disch note titles
  • Li/
    • ipynb about comorbidity index
    • SQL for SPADE data?
  • Maxxxx/
    • ipynb continuing Justin's UMAP of CUIs. Outlier disch summaries.
    • UMAP of structured "B00" data
  • Paarth/
    • ipynb to input CSV, output SQL
    • SQL with ICD groupers, SPADE-related

Note: the SPADE comorbidity index is calculated using SQL code from a different repo. Two files named proto_sf_calc_elix.sql and table_sf_calc_elix.sql.

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