A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions

Abstract

Deep learning algorithms trained on data streamed temporally from different clinical sites and from a multitude of physiological sensors are generally affected by a degradation in performance. To mitigate this, the authors propose a continual learning strategy that employs a replay buffer.