Upload model

modelling_cxrmate_ed.py

@@ -1111,9 +1111,16 @@ class MIMICIVEDCXRMultimodalModel(VisionEncoderDecoderModel):
                 connect.sql(f"CREATE TABLE {k}_study_ids AS SELECT * FROM df")
 
     @staticmethod                
-    def get_dataset(split, transforms, database_path, mimic_cxr_jpg_dir, max_images_per_study=5):
-                
-        records = EDCXRSubjectRecords(database_path=database_path, time_delta_map=lambda x: 1 / math.sqrt(x + 1)) 
+    def get_dataset(split, transforms, database_path, mimic_cxr_jpg_dir, max_images_per_study=5, records=None):
+        
+        if records is None:
+            
+            # This is the setup for CXRs + all effective inputs - medicine reconciliation:
+            records = EDCXRSubjectRecords(database_path=database_path, time_delta_map=lambda x: 1 / math.sqrt(x + 1)) 
+            
+            records.ed_module_tables = {k: records.ed_module_tables[k] for k in ['edstays', 'triage', 'vitalsign']}
+            records.mimic_cxr_tables = {k: records.mimic_cxr_tables[k] for k in ['mimic_cxr_sectioned']}
+            records.mimic_cxr_tables['mimic_cxr_sectioned'].text_columns = ['indication', 'history']
         
         dataset = StudyIDEDStayIDSubset(
                 mimic_iv_duckdb_path=database_path,