Update app.py

app.py

@@ -46,23 +46,26 @@ st.markdown(
 )
 st.sidebar.markdown('Using transformer model')
 
-## Loading in dataset
+## ======== Loading dataset ========
+## Loading in Admission Dataset
 df = pd.read_csv('shpi25nov.csv')
 
-#Loading in Admission chief Complaint and diagnosis
+# Loading in Admission chief Complaint and diagnosis
 df2 = pd.read_csv('cohort_cc_adm_diag.csv')
 
-#Loading in Dischare History
+# Loading in Dischare History
 df3 = pd.read_csv('cohort_past_history_12072022.csv')
 
-#combining both data into one 
+# combining both data into one 
 df = pd.merge(df, df2, on=['HADM_ID','SUBJECT_ID'])
 
+# Deleting admission chief complaint and diagnosis after combining
+del df2
+
+# Remove decimal point from Admission ID
 df['HADM_ID'] = df['HADM_ID'].astype(str).apply(lambda x: x.replace('.0',''))
 df3['HADM_ID'] = df3['HADM_ID'].astype(str).apply(lambda x: x.replace('.0',''))
 
-del df2
-
 #Renaming column
 df.rename(columns={'SUBJECT_ID':'Patient_ID',
                   'HADM_ID':'Admission_ID',
@@ -70,24 +73,25 @@ df.rename(columns={'SUBJECT_ID':'Patient_ID',
                   'hpi_reference_summary':'Reference_text'}, inplace = True)
 df3.rename(columns={'SUBJECT_ID':'Patient_ID'}, inplace = True) 
 
- #data.rename(columns={'gdp':'log(gdp)'}, inplace=True)
-
 #Filter selection 
 st.sidebar.header("Search for Patient:")
 
+# ===== Initial filter for patient and admission id =====
 patientid = df['Patient_ID']
-patient = st.sidebar.selectbox('Select Patient ID:', patientid)
-admissionid = df['Admission_ID'].loc[df['Patient_ID'] == patient]
-HospitalAdmission = st.sidebar.selectbox(' ', admissionid)
-pastHistoryEpid = df3['HADM_ID'].loc[df3['Patient_ID'] == patient]
+patient = st.sidebar.selectbox('Select Patient ID:', patientid)    #Filter Patient
+admissionid = df['Admission_ID'].loc[df['Patient_ID'] == patient]  #Filter available Admission id for patient
+HospitalAdmission = st.sidebar.selectbox(' ', admissionid)         
+pastHistoryEpid = df3['HADM_ID'].loc[df3['Patient_ID'] == patient] #Filter list of available Past History (for History tab)
 
 
 # List of Model available
 model = st.sidebar.selectbox('Select Model', ('BertSummarizer','BertGPT2','t5seq2eq','t5','gensim','pysummarizer'))
 
+# ===== to display selected patient and admission id on main page
 col3,col4 = st.columns(2) 
 patientid = col3.write(f"Patient ID:  {patient} ")
 admissionid =col4.write(f"Admission ID:  {HospitalAdmission} ")
+
 runtext = ''
 inputNote  ='Input note here:'
 # Query out relevant Clinical notes
@@ -147,6 +151,8 @@ with st.container():
             #st.date_input('Select Admission Date') # To replace with a dropdown filter instead 
             #st.selectbox('Past Episodes',pastHistoryEp)
             pastHistory = st.selectbox(' ', pastHistoryEpid)
+
+
     
 ##========= END on Past History Tab  =========
 
@@ -302,7 +308,11 @@ with col1:
         st.text_area('Reference text', str(reference_text), height=150)
     else: 
         with st.expander('Full Discharge Summary'):
-            st.write( str(original_text2))
+            historyAdmission =  df.query(
+                "Patient_ID  == @patient & Admission_ID == @pastHistory"
+                )
+            fulldischargesummary = historyAdmission['TEXT'].values
+            st.write( str(fulldischargesummary))
     ##====== Storing the Diseases/Text
     table= {"Entity":[], "Class":[]}
     ent_bc = {}