Edit user info for file upload in ml scores

Author: gurayerus

src/viewer/pages/workflow_sMRI_MLScores.py

@@ -99,6 +99,54 @@
                 p_demog = st.session_state.paths["csv_demog"]
                 st.success(f"Data is ready ({p_demog})", icon=":material/thumb_up:")
 
+        # Check the input data
+        @st.dialog("Input data requirements")  # type:ignore
+        def help_input_data():
+            df_muse = pd.DataFrame(
+                columns=['MRID', '702', '701', '600', '601', '...'],
+                data=[
+                    ['Subj1', '...', '...', '...', '...', '...'], 
+                    ['Subj2', '...', '...', '...', '...', '...'], 
+                    ['Subj3', '...', '...', '...', '...', '...'], 
+                    ['...', '...', '...', '...', '...', '...']
+                ]
+            )
+            st.markdown(
+                """
+                ### DLMUSE File: 
+                The DLMUSE CSV file contains volumes of ROIs (Regions of Interest) segmented by the DLMUSE algorithm. This file is generated as output when DLMUSE is applied to a set of images.
+                """
+            )
+            st.write('Example MUSE data file:')
+            st.dataframe(df_muse)
+
+            df_demog = pd.DataFrame(
+                columns=['MRID', 'Age', 'Sex'],
+                data=[
+                    ['Subj1', '57', 'F'], 
+                    ['Subj2', '65', 'M'], 
+                    ['Subj3', '44', 'F'], 
+                    ['...', '...', '...']
+                ]
+            )
+            st.markdown(
+                """
+                ### Demographics File: 
+                The DEMOGRAPHICS CSV file contains demographic information for each subject in the study.
+                - **Required Columns:**
+                    - **MRID:** Unique subject identifier.
+                    - **Age:** Age of the subject.
+                    - **Sex:** Sex of the subject (e.g., M, F).
+                - **Matching MRIDs:** Ensure the MRID values in this file match the corresponding MRIDs in the DLMUSE file for merging the data files.
+                """
+            )
+            st.write('Example demographic data file:')
+            st.dataframe(df_demog)
+
+        
+        if st.button('I need help 🤔'):
+            help_input_data()
+
         # Check the input data
         if st.button('Verify input data'):
             [f_check, m_check] = w_mlscores.check_input(

src/viewer/utils/utils_st.py

@@ -188,10 +188,10 @@ def util_panel_workingdir(app_type: str) -> None:
 
     # Read dataset name (used to create a folder where all results will be saved)
     helpmsg = (
-        "Each study's results are organized in a dedicated folder named after the study"
+        "Please provide a unique identifier for your experiment.\n\n A dedicated folder with this name will be created to store all input and output data associated with the analysis.\n\n The identifier can be any descriptive label; it doesn't need to match the input study or dataset name.\n\n Switch between experiments to run different pipelines or analyze new datasets."
     )
     st.session_state.dset = user_input_textfield(
-        "Study name", st.session_state.dset, helpmsg, False
+        "Experiment Identifier", st.session_state.dset, helpmsg, False
     )
 
     if app_type == "desktop":