Detecting atrial fibrillation by deep convolutional neural networks.
Journal:
Computers in biology and medicine
Published Date:
Dec 15, 2017
Abstract
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning.