Jeffrey Annis

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms

Contrastive learning is a widely adopted self-supervised pretraining strategy, yet its dependence on cohort composition remains underexplored. We present Contrasting by Augmented Patient Electrocardiograms (CAPE) foundation model and pretrain on four cohorts (n = 5,203,269), from...