Wp/add xray to multimodal task

.gitignore

@@ -136,4 +136,7 @@ pyhealth/medcode/pretrained_embeddings/kg_emb/examples/pretrained_model
 data/physionet.org/
 
 # VSCode settings
-.vscode/
+.vscode/
+
+# Local Data
+local_data/

docs/api/tasks.rst

@@ -99,3 +99,4 @@ Available Tasks
     Mutation Pathogenicity (COSMIC) <tasks/pyhealth.tasks.MutationPathogenicityPrediction>
     Cancer Survival Prediction (TCGA) <tasks/pyhealth.tasks.CancerSurvivalPrediction>
     Cancer Mutation Burden (TCGA) <tasks/pyhealth.tasks.CancerMutationBurden>
+    Multimodal Mortality Prediction (MIMIC-IV) <tasks/pyhealth.tasks.multimodal_mimic4>

docs/api/tasks/pyhealth.tasks.multimodal_mimic4.rst

@@ -0,0 +1,12 @@
+pyhealth.tasks.multimodal_mimic4
+===================================
+
+.. autoclass:: pyhealth.tasks.multimodal_mimic4.ClinicalNotesMIMIC4
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. autoclass:: pyhealth.tasks.multimodal_mimic4.ClinicalNotesICDLabsMIMIC4
+    :members:
+    :undoc-members:
+    :show-inheritance:

examples/mortality_prediction/multimodal_mimic4.py

@@ -0,0 +1,84 @@
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+import os
+
+# PyHealth Packages
+from pyhealth.datasets import MIMIC4Dataset
+from pyhealth.tasks.multimodal_mimic4 import ClinicalNotesMIMIC4, ClinicalNotesICDLabsMIMIC4, ClinicalNotesICDLabsCXRMIMIC4
+from pyhealth.tasks.base_task import BaseTask
+
+# Load MIMIC4 Files
+# There's probably better ways dealing with this on the cluster, but working locally for now 
+# (see: https://github.com/sunlabuiuc/PyHealth/blob/master/examples/mortality_prediction/multimodal_mimic4_minimal.py)
+
+TASK = "ClinicalNotesICDLabsCXRMIMIC4" # The idea here is that we want additive tasks so we can evaluate the value in adding more modalities
+
+PYHEALTH_REPO_ROOT = '/Users/wpang/Desktop/PyHealth'
+
+EHR_ROOT = os.path.join(PYHEALTH_REPO_ROOT, "local_data/local/data/physionet.org/files/mimiciv/2.2")
+NOTE_ROOT = os.path.join(PYHEALTH_REPO_ROOT, "local_data/local/data/physionet.org/files/mimic-iv-note/2.2")
+CXR_ROOT = os.path.join(PYHEALTH_REPO_ROOT,"local_data/local/data/physionet.org/files/mimic-cxr-jpg/2.0.0")
+CACHE_DIR = os.path.join(PYHEALTH_REPO_ROOT,"local_data/local/data/wp/pyhealth_cache")
+
+DEV_MODE = True
+
+if __name__ == "__main__":
+
+    if TASK == "ClinicalNotesMIMIC4": # A bit janky setup at the moment and open to iteration, but conveys the point for now
+        dataset = MIMIC4Dataset(
+                ehr_root=EHR_ROOT,
+                note_root=NOTE_ROOT,
+                ehr_tables=["diagnoses_icd", "procedures_icd", "prescriptions", "labevents"],
+                note_tables=["discharge", "radiology"],
+                cache_dir=CACHE_DIR,
+                num_workers=8,
+                dev=DEV_MODE
+            )
+
+        # Apply multimodal task
+        task = ClinicalNotesMIMIC4() 
+        samples = dataset.set_task(task)
+
+        # Get and print sample
+        sample = samples[0]
+        print(sample)
+
+    elif TASK == 'ClinicalNotesICDLabsMIMIC4':
+        dataset = MIMIC4Dataset(
+                ehr_root=EHR_ROOT,
+                note_root=NOTE_ROOT,
+                ehr_tables=["diagnoses_icd", "procedures_icd", "prescriptions", "labevents"],
+                note_tables=["discharge", "radiology"],
+                cache_dir=CACHE_DIR,
+                num_workers=8,
+                dev=DEV_MODE
+            )
+
+        # Apply multimodal task
+        task = ClinicalNotesICDLabsMIMIC4() 
+        samples = dataset.set_task(task)
+
+        # Get and print sample
+        sample = samples[0]
+        print(sample)
+
+    elif TASK == 'ClinicalNotesICDLabsCXRMIMIC4':
+        dataset = MIMIC4Dataset(
+                ehr_root=EHR_ROOT,
+                note_root=NOTE_ROOT,
+                cxr_root=CXR_ROOT,
+                ehr_tables=["diagnoses_icd", "procedures_icd", "prescriptions", "labevents"],
+                note_tables=["discharge", "radiology"],
+                cxr_tables=["metadata", "negbio"],
+                cache_dir=CACHE_DIR,
+                num_workers=8,
+                dev=DEV_MODE
+            )
+
+        # Apply multimodal task
+        task = ClinicalNotesICDLabsCXRMIMIC4() 
+        samples = dataset.set_task(task)
+
+        # Get and print sample
+        sample = samples[0]
+        print(sample)