Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial-Reference-Cited by-同舟云学术

Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial

Published:2021-05 Issue:5 Volume:27 Page:815-819
ISSN:1078-8956
Container-title:Nature Medicine
language:en
Short-container-title:Nat Med

Author:

Yao Xiaoxi^ORCID,Rushlow David R.,Inselman Jonathan W.,McCoy Rozalina G.,Thacher Thomas D.^ORCID,Behnken Emma M.,Bernard Matthew E.,Rosas Steven L.,Akfaly Abdulla,Misra Artika,Molling Paul E.,Krien Joseph S.,Foss Randy M.^ORCID,Barry Barbara A.,Siontis Konstantinos C.,Kapa Suraj,Pellikka Patricia A.^ORCID,Lopez-Jimenez Francisco,Attia Zachi I.^ORCID,Shah Nilay D.,Friedman Paul A.^ORCID,Noseworthy Peter A.^ORCID

Funder

Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

Link

http://www.nature.com/articles/s41591-021-01335-4.pdf

Reference24 articles.

1. Wang, T. J. et al. Natural history of asymptomatic left ventricular systolic dysfunction in the community. Circulation 108, 977–982 (2003).

2. McDonagh, T. A. et al. Symptomatic and asymptomatic left-ventricular systolic dysfunction in an urban population. Lancet 350, 829–833 (1997).

3. Redfield, M. M. et al. Burden of systolic and diastolic ventricular dysfunction in the community: appreciating the scope of the heart failure epidemic. JAMA 289, 194–202 (2003).