Merge pull request #23 from eipm/B2AI-541

B2AI-541

src/tabs/collection_methods.py

@@ -41,7 +41,7 @@ def collection_methods_page(tab_name):
 
     csv_file_path = "tables/Disease_cohort_inclusion_exclusion_criteria.csv"
     caption = 'Table 1 - Disease cohort inclusion/exclusion criteria and validation methods'
-    create_html_table(csv_file_path, caption)
+    create_html_table(csv_file_path, caption, [], 0)
 
     csv_file_path = "tables/Acoustic_Tasks_Protocol.csv"
     caption = 'Table 2 - Acoustic Tasks in Protocol'

src/tabs/study_metadata.py

@@ -1,6 +1,119 @@
 import streamlit as st
 from tabs.utils import coming_soon_message
+from tabs.utils import create_html_table
+
+def show_table(key, button_text, show_table, csv_file_path, caption):
+        if st.button(button_text, key):
+            st.session_state[show_table] = not st.session_state[show_table]
+
+        # Conditionally display the table
+        if st.session_state[show_table]:
+            create_html_table(csv_file_path, caption, [], 0)
 
 # Define the content of the Study Metadata page
 def study_metadata_page(tab_name):
-    coming_soon_message(tab_name)
+
+    # Initialize session state for table visibility
+    if 'show_table_1' not in st.session_state:
+        st.session_state['show_table_1'] = False
+
+    st.markdown(
+    """
+    Official Title:  Bridge2AI-Voice
+
+    Design: Study Type - Observational
+    
+    Enrollment Count (Anticipated by 2027): 10,000
+    
+    Design Observation Model
+    - Cohort
+    
+    Design Time Perspective
+    - Cross-sectional
+    
+    Biospecimens: Respiratory, Voice and speech samples
+    
+    Biospecimens Description<br>
+    The Bridge2AI-Voice dataset contains samples from conventional acoustic tasks including respiratory sounds, cough sounds, and free speech prompts, capturing voice, speech and language data relating to health. Participants who consent are asked to perform speaking tasks and complete self-reported demographic and medical history questionnaires, as well as disease-specific validated questionnaires. Participants who consent also permit investigators to access medical information through EHR platforms in order to perform gold standard validation of diagnoses and symptoms  
+    
+    <ins>Eligibility</ins>
+
+    Sex<br>
+    All
+
+    Gender Based<br>
+    No
+
+    Minimum Age<br>
+    18 years (this will change when pediatric cohort is introduced, and metadata will be updated to reflect new eligibility criteria) 
+
+    Maximum Age<br>
+    120 years 
+
+    Healthy Volunteers<br>
+    Yes 
+
+    Inclusion Criteria<br>""", unsafe_allow_html=True)
+
+    show_table(1, 'See Collection Methods - Table 1', 'show_table_1', "tables/Disease_cohort_inclusion_exclusion_criteria.csv", 'Table 1 - Disease cohort inclusion/exclusion criteria and validation methods')
+
+    st.markdown(
+    """
+    Exclusion Criteria<br>
+    Does not read or speak English (Please note, the Spanish protocols and Data collection will be included in future releases)<br>""", unsafe_allow_html=True)
+
+    show_table(2, 'See Collection Methods - Table 1', 'show_table_1', "tables/Disease_cohort_inclusion_exclusion_criteria.csv", 'Table 1 - Disease cohort inclusion/exclusion criteria and validation methods')
+
+    st.markdown(
+    """
+    Study Population<br>
+    The current v.1.0.0 dataset contains only adult populations. As the study progresses, a pediatric cohort will be introduced. Inclusion/exclusion criteria and additional information regarding the dataset and study metadata will be updated at that time. In addition, the current dataset contains fluent English speakers but will expand to include data collection in Spanish.
+
+    Sampling Method<br>
+    Non-Probability Sample<br>
+    Identification Information<br>
+    Organization Study ID<br>
+    OT2OD032720<br>
+    
+    Organization Study Type<br>
+    U.S. National Institutes of Health (NIH) Grant/Contract Award Number
+    
+    Secondary ID<br>
+    <table style="border: none;">
+    <tr>
+    <td><b>ID</b></td>
+    <td><b>Link</b></td>
+    </tr>
+    <tr>
+    <td>OT2OD032720</td>
+    <td><a href="https://reporter.nih.gov/search/4XtcXzBGEkWQlwG5v8odBA/project-details/10858564">https://reporter.nih.gov/search/4XtcXzBGEkWQlwG5v8odBA/project-details/10858564</a></td>
+    </tr>
+    </table>
+    
+    Collaborators 
+    - University of South Florida 
+    - Weill Cornell Medicine 
+    - Oregon Health & Science University
+    - Massachusetts Institute of Technology 
+    - University of Toronto 
+    - Mount Sinai Hospital
+    - Hospital for Sick Children
+    - Simon Fraser University 
+    - The Hastings Center 
+    - Washington University in St. Louis 
+    - University of Florida
+    - Vanderbilt University Medical Center
+
+    URL 
+    How to cite
+    If you use this dataset for any purpose, please cite the resources specified in the Bridge2AI-Voice documentation for version 1.0.0 of the dataset at (URL)
+    
+    Bridge2AI-Voice Consortium (2024). Flagship Voice Dataset from the Bridge2AI-Voice Project (1.0.0) [Dataset]. 
+
+    Contact
+    For any questions, suggestions, or feedback related to this dataset, please email [email protected]
+    
+    Acknowledgement
+    Bridge2AI-Voice is supported by NIH grant OT2OD032720 through the NIH Bridge2AI Common Fund program.
+    """, unsafe_allow_html=True)
+

src/tabs/utils.py

@@ -9,15 +9,22 @@ def coming_soon_message(tab_name):
     image_path = "images/Wave.png"
     st.image(image_path, caption='', use_container_width=True)
 
-def create_html_table(csv_file_path, caption=None, cell_values=[]):
-       # Read CSV file
+def create_html_table(csv_file_path, caption=None, cell_values=[], column_index=-1):
+    # Read CSV file
     df = pd.read_csv(csv_file_path, dtype=str)  # Ensure all columns are read as strings
 
     # Replace NaN with an empty string;
     df = df.fillna("")
-
+
+    bold_cells = df.iloc[:, column_index].tolist() if column_index >= 0 else []
+
     # Convert DataFrame to HTML table
     html_table = df.to_html(index=False, classes='table table-striped')
+
+    if bold_cells and len(bold_cells) > 0:
+        for bold_cell in bold_cells:
+            html_table = html_table.replace(f'<td>{bold_cell}</td>', f'<td class="bold-cell">{bold_cell}</td>')
+
     if cell_values and len(cell_values) > 0:
         for cell_value in cell_values:
             html_table = html_table.replace(f'<td>{cell_value}</td>', f'<td class="center-align">{cell_value}</td>')
@@ -51,9 +58,18 @@ def create_html_table(csv_file_path, caption=None, cell_values=[]):
             padding: 4px !important;
             text-align: left;
         }
+        
+        .table th {
+            background-color: #f2f2f2;
+        }
+        
         .table .center-align {
             text-align: center; /* Center alignment for specific columns */
         }
+        
+        .table .bold-cell {
+            font-weight: bold; /* Bold font for first column cells */
+        }
         </style>
         """,
         unsafe_allow_html=True