Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction-Reference-Cited by-同舟云学术

Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction

Published:2021-06-01 Issue:6 Volume:6 Page:633
ISSN:2380-6583
Container-title:JAMA Cardiology
language:en
Short-container-title:JAMA Cardiol

Author:

Khera Rohan¹²,Haimovich Julian³,Hurley Nathan C.⁴,McNamara Robert¹,Spertus John A.⁵⁶,Desai Nihar¹²,Rumsfeld John S.⁷,Masoudi Frederick A.⁷,Huang Chenxi²,Normand Sharon-Lise⁸⁹,Mortazavi Bobak J.⁴,Krumholz Harlan M.¹²¹⁰

Affiliation:

1. Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut

2. Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut

3. Department of Internal Medicine, Massachusetts General Hospital, Boston

4. Department of Computer Science and Engineering, Texas A&M University, College Station

5. Saint Luke's Mid America Heart Institute, Kansas City, Missouri

6. Division of Cardiology, Department of Internal Medicine, University of Missouri, Kansas City

7. Division of Cardiology, Department of Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora

8. Department of Biostatistics, T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts

9. Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts

10. Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut

Publisher

American Medical Association (AMA)

Subject

Cardiology and Cardiovascular Medicine

Link

https://jamanetwork.com/journals/jamacardiology/articlepdf/2777055/jamacardiology_khera_2021_oi_210003_1623268689.07933.pdf

Reference34 articles.

1. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE).;Fox;BMJ,2006

2. Predictors of hospital mortality in the global registry of acute coronary events.;Granger;Arch Intern Med,2003

3. The TIMI risk score for unstable angina/non-ST elevation MI: a method for prognostication and therapeutic decision making.;Antman;JAMA,2000

4. 5-year outcome of an interventional strategy in non-ST-elevation acute coronary syndrome: the British Heart Foundation RITA 3 randomised trial.;Fox;Lancet,2005

5. Bayesian binary regression model: an application to in-hospital death after AMI prediction.;Souza;Pesquisa Operacional,2004

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