sunlabuiuc · jiama843 · Mar 17, 2026 · Mar 17, 2026 · Mar 23, 2026 · Mar 25, 2026
diff --git a/docs/api/datasets.rst b/docs/api/datasets.rst
@@ -226,6 +226,7 @@ Available Datasets
     datasets/pyhealth.datasets.MIMIC4Dataset
     datasets/pyhealth.datasets.MedicalTranscriptionsDataset
     datasets/pyhealth.datasets.CardiologyDataset
+    datasets/pyhealth.datasets.Cardiology2Dataset
     datasets/pyhealth.datasets.eICUDataset
     datasets/pyhealth.datasets.ISRUCDataset
     datasets/pyhealth.datasets.MIMICExtractDataset

diff --git a/docs/api/datasets/pyhealth.datasets.Cardiology2Dataset.rst b/docs/api/datasets/pyhealth.datasets.Cardiology2Dataset.rst
@@ -0,0 +1,11 @@
+pyhealth.datasets.Cardiology2Dataset
+=====================================
+
+The PhysioNet/Computing in Cardiology Challenge 2020 dataset of 12-lead ECG recordings.
+
+For more information, refer to `PhysioNet page <https://physionet.org/content/challenge-2020/1.0.2/>`.
+
+.. autoclass:: pyhealth.datasets.Cardiology2Dataset
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/api/tasks.rst b/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>
+    Cardiology Multilabel Classification <tasks/pyhealth.tasks.CardiologyMultilabelClassification>
     COVID-19 CXR Classification <tasks/pyhealth.tasks.COVID19CXRClassification>
     DKA Prediction (MIMIC-IV) <tasks/pyhealth.tasks.dka>
     Drug Recommendation <tasks/pyhealth.tasks.drug_recommendation>

diff --git a/docs/api/tasks/pyhealth.tasks.CardiologyMultilabelClassification.rst b/docs/api/tasks/pyhealth.tasks.CardiologyMultilabelClassification.rst
@@ -0,0 +1,12 @@
+pyhealth.tasks.CardiologyMultilabelClassification
+==================================================
+
+Multi-label ECG classification over 24 SNOMED-CT diagnosis codes from the
+PhysioNet/Computing in Cardiology Challenge 2020 dataset. The task follows
+the benchmark protocol of `Nonaka & Seita (2021) <https://proceedings.mlr.press/v149/nonaka21a/nonaka21a.pdf>`,
+evaluated with macro-averaged ROC-AUC.
+
+.. autoclass:: pyhealth.tasks.CardiologyMultilabelClassification
+    :members:
+    :undoc-members:
+    :show-inheritance: