MIMIC4 Readmission Prediction

docs/api/tasks.rst

@@ -21,9 +21,9 @@ New to PyHealth tasks? Start here:
 - **Tutorial**: `Introduction to pyhealth.tasks <https://colab.research.google.com/drive/1kKkkBVS_GclHoYTbnOtjyYnSee79hsyT?usp=sharing>`_ - Learn the basics of defining and using tasks
 - **Code Examples**: Browse all examples online at https://github.com/sunlabuiuc/PyHealth/tree/master/examples
 - **Pipeline Examples**: Check out our :doc:`../tutorials` page for complete end-to-end examples including:
-  
+
   - Mortality Prediction Pipeline
-  - Readmission Prediction Pipeline  
+  - Readmission Prediction Pipeline
   - Medical Coding Pipeline
   - Chest X-ray Classification Pipeline
 
@@ -47,14 +47,14 @@ After you define a task:
     task = MortalityPredictionMIMIC4()
     # input_schema = {"conditions": "sequence", "procedures": "sequence"}
     # output_schema = {"mortality": "binary"}
-    
+
     # 2. Apply task to dataset
     sample_dataset = base_dataset.set_task(task)
-    
+
     # 3. Processors automatically transform samples:
     #    - "sequence" -> SequenceProcessor (converts codes to indices)
     #    - "binary" -> BinaryLabelProcessor (converts labels to tensors)
-    
+
     # 4. Get model-ready tensors
     sample = sample_dataset[0]
     # sample["conditions"] is now a tensor of token indices
@@ -74,7 +74,6 @@ Available Tasks
     :maxdepth: 3
 
     Base Task <tasks/pyhealth.tasks.BaseTask>
-    Readmission (30 Days, MIMIC-IV) <tasks/pyhealth.tasks.Readmission30DaysMIMIC4>
     In-Hospital Mortality (MIMIC-IV) <tasks/pyhealth.tasks.InHospitalMortalityMIMIC4>
     MIMIC-III ICD-9 Coding <tasks/pyhealth.tasks.MIMIC3ICD9Coding>
     Cardiology Detection <tasks/pyhealth.tasks.cardiology_detect>

docs/api/tasks/pyhealth.tasks.readmission_prediction.rst

@@ -6,7 +6,11 @@
     :undoc-members:
     :show-inheritance:
 
-.. autofunction:: pyhealth.tasks.readmission_prediction.readmission_prediction_mimic4_fn
+.. autoclass:: pyhealth.tasks.readmission_prediction.ReadmissionPredictionMIMIC4
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 .. autofunction:: pyhealth.tasks.readmission_prediction.readmission_prediction_eicu_fn
 .. autofunction:: pyhealth.tasks.readmission_prediction.readmission_prediction_eicu_fn2
 

examples/readmission/readmission_mimic4_rnn.py

@@ -0,0 +1,44 @@
+import tempfile
+
+from pyhealth.datasets import MIMIC4Dataset
+from pyhealth.datasets import split_by_patient, get_dataloader
+from pyhealth.models import RNN
+from pyhealth.tasks import ReadmissionPredictionMIMIC4
+from pyhealth.trainer import Trainer
+
+# Since PyHealth uses multiprocessing, it is best practice to use a main guard.
+if __name__ == '__main__':
+    # Use tempfile to automate cleanup
+    cache_dir = tempfile.TemporaryDirectory()
+
+    base_dataset = MIMIC4Dataset(
+        ehr_root="https://physionet.org/files/mimic-iv-demo/2.2/",
+        ehr_tables=["diagnoses_icd", "procedures_icd", "prescriptions"],
+        cache_dir=cache_dir.name
+    )
+    base_dataset.stats()
+
+    sample_dataset = base_dataset.set_task(ReadmissionPredictionMIMIC4())
+
+    train_dataset, val_dataset, test_dataset = split_by_patient(
+        sample_dataset, [0.8, 0.1, 0.1]
+    )
+    train_dataloader = get_dataloader(train_dataset, batch_size=32, shuffle=True)
+    val_dataloader = get_dataloader(val_dataset, batch_size=32, shuffle=False)
+    test_dataloader = get_dataloader(test_dataset, batch_size=32, shuffle=False)
+
+    model = RNN(
+        dataset=sample_dataset,
+    )
+
+    trainer = Trainer(model=model)
+    trainer.train(
+        train_dataloader=train_dataloader,
+        val_dataloader=val_dataloader,
+        epochs=1,
+        monitor="roc_auc",
+    )
+
+    trainer.evaluate(test_dataloader)
+
+    sample_dataset.close()

pyhealth/tasks/__init__.py

@@ -50,12 +50,11 @@
     MortalityPredictionStageNetMIMIC4,
 )
 from .patient_linkage import patient_linkage_mimic3_fn
-from .readmission_30days_mimic4 import Readmission30DaysMIMIC4
 from .readmission_prediction import (
     ReadmissionPredictionMIMIC3,
+    ReadmissionPredictionMIMIC4,
     readmission_prediction_eicu_fn,
     readmission_prediction_eicu_fn2,
-    readmission_prediction_mimic4_fn,
     ReadmissionPredictionOMOP,
 )
 from .sleep_staging import (