Add ECGMultiLabelCardiologyTask

docs/api/tasks.rst

@@ -209,6 +209,7 @@ Available Tasks
     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>
+    ECG Multi-Label Cardiology Task <tasks/pyhealth.tasks.ecg_classification>
     COVID-19 CXR Classification <tasks/pyhealth.tasks.COVID19CXRClassification>
     DKA Prediction (MIMIC-IV) <tasks/pyhealth.tasks.dka>
     Drug Recommendation <tasks/pyhealth.tasks.drug_recommendation>

docs/api/tasks/pyhealth.tasks.ecg_classification.rst

@@ -0,0 +1,94 @@
+pyhealth.tasks.ecg_classification
+=================================
+
+.. currentmodule:: pyhealth.tasks.ecg_classification
+
+ECG Multi-Label Cardiology Task
+-------------------------------
+
+This module provides an implementation of a multi-label ECG classification task
+for the PyHealth framework.
+
+The task processes 12-lead electrocardiogram (ECG) signals and predicts
+multiple cardiac conditions simultaneously. It extends the PyHealth
+``BaseTask`` class and integrates with PyHealth datasets and models.
+
+Key Features
+------------
+
+- Multi-label classification support
+- PhysioNet-style ECG file handling (``.mat`` and ``.hea``)
+- Sliding window segmentation
+- Metadata extraction (age, sex, diagnosis codes)
+- Compatibility with PyHealth pipelines
+
+Input Format
+------------
+
+Each patient visit is represented as a dictionary:
+
+.. code-block:: python
+
+    {
+        "load_from_path": "...",
+        "patient_id": "...",
+        "signal_file": "record.mat",
+        "label_file": "record.hea",
+    }
+
+Output Format
+-------------
+
+Each processed sample contains:
+
+.. code-block:: python
+
+    {
+        "signal": numpy.ndarray,
+        "label": numpy.ndarray,
+        "patient_id": str,
+        "visit_id": str,
+        "record_id": str,
+        "Sex": str,
+        "Age": int,
+    }
+
+Parameters
+----------
+
+- ``labels``: list of target diagnosis labels
+- ``epoch_sec``: window size in seconds
+- ``shift``: step size between windows
+- ``sampling_rate``: signal sampling frequency
+
+Ablation Support
+----------------
+
+This task enables experimentation across:
+
+- Label set variation
+- Temporal segmentation
+
+Example
+-------
+
+.. code-block:: python
+
+    from pyhealth.tasks.ecg_classification import ECGMultiLabelCardiologyTask
+
+    task = ECGMultiLabelCardiologyTask(
+        labels=["AF", "RBBB"],
+        epoch_sec=10,
+        shift=5,
+        sampling_rate=500,
+    )
+
+    samples = task(visit_dict)
+
+Module Reference
+----------------
+
+.. automodule:: pyhealth.tasks.ecg_classification
+   :members:
+   :undoc-members:
+   :show-inheritance: