Prospective validation of a deep learning electrocardiogram algorithm for the detection of left ventricular systolic dysfunction

Objectives We sought to validate a deep learning algorithm designed to predict an ejection fraction (EF) less than or equal to 35% based on the 12‐lead electrocardiogram (ECG) in a large prospective cohort. Background Patients undergoing routine ECG may have undetected left ventricular (LV) dysfunct...

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Bibliographic Details
Published in:	Journal of cardiovascular electrophysiology Vol. 30; no. 5; pp. 668 - 674
Main Authors:	Attia, Zachi I., Kapa, Suraj, Yao, Xiaoxi, Lopez‐Jimenez, Francisco, Mohan, Tarun L., Pellikka, Patricia A., Carter, Rickey E., Shah, Nilay D., Friedman, Paul A., Noseworthy, Peter A.
Format:	Journal Article
Language:	English
Published:	United States Wiley Subscription Services, Inc 01.05.2019
Subjects:	Algorithms artificial intelligence Deep learning Echocardiography ejection fraction EKG electrocardiogram Electrocardiography Heart Ultrasonic imaging Ventricle deep learning electrocardiogram ejection fraction artificial intelligence echocardiography
ISSN:	1045-3873, 1540-8167, 1540-8167
Online Access:	Get full text
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