Detection and classification of arrhythmia using an explainable deep learning model.
Journal:
Journal of electrocardiology
Published Date:
Jun 26, 2021
Abstract
BACKGROUND: Early detection and intervention is the cornerstone for appropriate treatment of arrhythmia and prevention of complications and mortality. Although diverse deep learning models have been developed to detect arrhythmia, they have been criticized due to their unexplainable nature. In this study, we developed an explainable deep learning model (XDM) to classify arrhythmia, and validated its performance using diverse external validation data.