Broad Institute (ML4H)
Multi-task 12-lead ECG model with output heads for incident atrial-fibrillation risk (as a survival curve), incident mortality risk, prevalent AF classification, sex classification, and age regression. Built on a 1D CNN over the raw waveform, and developed by the Broad Institute's ML4H group as a successor to their ECG-AI model published in Circulation. Trained on ECGs from UK Biobank and Massachusetts General Hospital, neither of which is publicly released.
Architecture
CNN (1D)
1D CNN over 12-lead, 5000-sample ECG waveform with 4-5 output heads
Framework
TensorFlow
Added to catalog
2026-07-10
GPL 3.0
License for model weights only. Associated code may be licensed seperately, check code source for specific terms.
Massachusetts General Hospital Primary Care ECG Cohort (ECG2AF)
100,954 ECGs from 45,770 individuals
UK Biobank ECG External Test Cohort (ECG2AF)
Multi-label classification
Multi-label classification