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Cardiovascular artificial intelligence models for discovery, comparison, and reuse

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Catalog maintained by the Fahed Lab

CVAI Catalog © 2026 Broad Institute

DeepECG-SL

EfficientNetV2 (supervised)

Montreal Heart Institute (HeartWise.AI) (Avram et al.)

12-lead ECG

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ECG

General Purpose / Multi-task

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General / Foundation

LV systolic dysfunction (LVSD)

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Cardiac Function & Hemodynamics

Atrial fibrillation

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Arrhythmia

Long QT syndrome (LQTS)

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Arrhythmia

Multi-label classification

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Classification

Binary classification

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Classification

Multi-class classification

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Classification

CNN (2D)

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Convolutional (CNN)

PyTorch

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PyTorch

Apache 2.0

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Permissive

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Supervised EfficientNetV2-based 12-lead ECG model trained on over 1 million ECGs from the Montreal Heart Institute to predict 77 cardiac conditions derived from American Heart Association recommendations, plus fine-tuned digital-biomarker heads for reduced LVEF, 5-year atrial-fibrillation risk, and long-QT-syndrome (LQTS) detection/genotyping. Validated on 881,403 ECGs across 11 geographically diverse cohorts (4 public, 7 private health systems), achieving AUROCs above 0.98 for the 77-condition interpretation task while being 60x smaller and 29x faster at inference than its self-supervised DeepECG-SSL counterpart, with up to 9.7x lower CO2 emissions on equivalent tasks.

memory Specifications

category

Architecture

CNN (2D)

EfficientNetV2 2D-CNN backbone applied to 12-lead ECG, trained with standard supervised multi-label classification on 77 AHA-derived cardiac conditions plus task-specific fine-tuned heads (LVEF<=40%, 5-year AF risk, LQTS)

code

Framework

PyTorch

calendar_month

Added to catalog

2026-08-10

gavel License

Apache 2.0

check_small Open source check_small Commercial use OK check_small Modifications allowed Attribution required No share-alike requirement

License for model weights only. Associated code may be licensed seperately, check code source for specific terms.

description Publication

Foundation models for electrocardiogram interpretation: clinical implications open_in_new

European Heart Journal · 2026 · original paper

DOI: 10.1093/eurheartj/ehaf1119

database Training & evaluation data

DeepECG Multi-Site External Validation Cohort

test

Aggregate of 11 geographically diverse external validation cohorts totaling 881,403 ECGs: four public datasets (UK Biobank, Canadian Longitudinal Study on Aging [CLSA], MIMIC-IV, PTB) and seven private health-system datasets (UCSF, MGH, Cedars-Sinai, JGH, UW, NYP, CHUM).

Montreal Heart Institute ECG Database (MHI-ds)

train

public 184,210 subjects · Canada

Over 1,000,000 12-lead ECGs from 184,210 patients treated at the Montreal Heart Institute, with automated free-text extraction of 77 AHA-derived diagnostic labels from ECG reports; primary training data for DeepECG-SL and part of the DeepECG-SSL pretraining corpus.

science Capabilities & performance

Multi-label 12-lead ECG interpretation across 77 AHA-derived cardiac conditions

Multi-label classification General Purpose / Multi-task
0.992 AUROC MHI-ds internal test · internal
0.98 AUROC External public datasets (UKB, CLSA, MIMIC-IV, PTB) · external
0.983 AUROC External private health-center datasets (UW, UCSF, JGH, NYP, MGH, CSH, CHUM) · external

Reduced LVEF (<=40%) classification from 12-lead ECG

Binary classification LV systolic dysfunction (LVSD)
0.917 AUROC DeepECG external validation (LVEF<=40%) · external

5-year atrial fibrillation risk prediction from 12-lead ECG

Binary classification Atrial fibrillation
0.734 AUROC DeepECG external validation (5-year AF risk) · external

Long QT syndrome (LQTS) detection from 12-lead ECG

Binary classification Long QT syndrome (LQTS)
0.735 AUROC DeepECG external validation (LQTS detection) · external

Long QT syndrome (LQTS) genotype classification from 12-lead ECG

Multi-class classification Long QT syndrome (LQTS)
0.85 AUROC DeepECG external validation (LQTS genotype) · external