Biometric contrastive learning for data-efficient deep learning from electrocardiographic images

Veer Sangha, Akshay Khunte, Gregory Holste, Bobak J. Mortazavi, Zhangyang Wang, Evangelos K. Oikonomou, Rohan Khera

Abstract: Artificial intelligence (AI) detects heart disease from images of electrocardiograms (ECGs). However, traditional supervised learning is limited by the need for large amounts of labeled data. We report the development of Biometric Contrastive Learning (BCL), a self-supervised pretraining approach for label-efficient deep learning on ECG images.