A contrastive-learning ECG foundation model with multitask heads predicts post-MI outcomes better than training from scratch (AUC 0.794 vs 0.608).
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Dynamical Predictive Modelling of Cardiovascular Disease Progression Post-Myocardial Infarction via ECG-Trained Artificial Intelligence Model
A contrastive-learning ECG foundation model with multitask heads predicts post-MI outcomes better than training from scratch (AUC 0.794 vs 0.608).