Association of Machine Learning–Derived Phenogroupings of Echocardiographic Variables with Heart Failure in Stable Coronary Artery Disease: The Heart and Soul Study-Reference-Cited by-同舟云学术

Association of Machine Learning–Derived Phenogroupings of Echocardiographic Variables with Heart Failure in Stable Coronary Artery Disease: The Heart and Soul Study

Published:2020-03 Issue:3 Volume:33 Page:322-331.e1
ISSN:0894-7317
Container-title:Journal of the American Society of Echocardiography
language:en
Short-container-title:Journal of the American Society of Echocardiography

Author:

Mishra Rakesh K.,Tison Geoffrey H.^ORCID,Fang Qizhi,Scherzer Rebecca^ORCID,Whooley Mary A.,Schiller Nelson B.

Funder

National Institutes of Health

Department of Veterans Affairs

National Heart, Lung, and Blood Institute

American Federation for Aging Research

Robert Wood Johnson Foundation

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine,Radiology Nuclear Medicine and imaging

Reference29 articles.

1. Usefulness of left atrial volume index to predict heart failure hospitalization and mortality in ambulatory patients with coronary heart disease and comparison to left ventricular ejection fraction (from the Heart and Soul Study);Ristow;Am J Cardiol,2008

2. Prognostic significance of increased left ventricular mass index to mortality and sudden death in patients with stable coronary heart disease (from the Heart and Soul Study);Turakhia;Am J Cardiol,2008

3. Left ventricular outflow tract and pulmonary artery stroke distances independently predict heart failure hospitalization and mortality: the Heart and Soul Study;Ristow;J Am Soc Echocardiogr,2011

4. Usefulness of diastolic dominant pulmonary vein flow to predict hospitalization for heart failure and mortality in ambulatory patients with coronary heart disease (from the Heart and Soul Study);Ren;Am J Cardiol,2009

5. Contribution of ischemic mitral regurgitation to congestive heart failure after myocardial infarction;Grigioni;J Am Coll Cardiol,2005

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