test

app.py

@@ -44,9 +44,9 @@ def load_data(data_dir : str,
     #Column rename
     df.rename(columns={'ID': 'patient_id', 'REAL_STONE':'target'}, inplace=True)
     
-    # feature importance w/o VISIBLE_STONE_CT(n=11)
-    columns = ['patient_id','DUCT_DILIATATION_8MM', 'DUCT_DILIATATION_10MM','Hb', 'PLT', 'WBC', 'ALP', 'ALT', 'AST', 'CRP', 'BILIRUBIN', 'AGE','target']
-      
+    # Final(n=11)
+    columns = ['patient_id','DUCT_DILIATATION_8MM', 'DUCT_DILIATATION_10MM','PANCREATITIS','FIRST_SBP','FIRST_RR','Hb', 'PLT', 'WBC', 'ALP', 'AST', 'CRP', 'BILIRUBIN', 'AGE','target']
+
     data = df[columns]
     data['patient_id'] = data['patient_id'].astype(str)
 
@@ -55,9 +55,10 @@ def load_data(data_dir : str,
     def get_patient_data(image_number):
         row = data[data['patient_id'].astype(str).str.startswith(image_number)]
         return row.iloc[0, 1:].tolist() if not row.empty else None
-    
-    # feature importance w/o VISIBLE_STONE_CT(n=11)
-    data_dict = {key: [] for key in ['image_path', 'DUCT_DILIATATION_8MM', 'DUCT_DILIATATION_10MM', 'Hb', 'PLT', 'WBC', 'ALP', 'ALT', 'AST', 'CRP', 'BILIRUBIN', 'AGE','target']}
+ 
+    # Final(n=11)
+    data_dict = {key: [] for key in ['image_path','DUCT_DILIATATION_8MM', 'DUCT_DILIATATION_10MM','PANCREATITIS','FIRST_SBP','FIRST_RR','Hb', 'PLT', 'WBC', 'ALP', 'AST', 'CRP', 'BILIRUBIN', 'AGE','target']}
+
 
     
     # Filter images based on the phase
@@ -100,6 +101,7 @@ def load_data(data_dir : str,
     if modality == 'tabular':
         train_df = data
 
+
     if mode == 'train' or mode == 'test':
         print("--------------Class balance--------------")
         # undersampling
@@ -155,7 +157,7 @@ def load_data(data_dir : str,
     
     
 def parse_args(args):
-    parser = argparse.ArgumentParser(description="M3D-LaMed chat")
+    parser = argparse.ArgumentParser(description="CBD Classification")
     parser.add_argument('--data_dir', type=str, default="./")
     parser.add_argument('--excel_file', type=str, default="dumc_1223_case3_duct_correct.csv")
     parser.add_argument('--modality', type=str, default="tabular")