Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model-Reference-Cited by-同舟云学术

Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model

Published:2021-06 Issue:6 Volume:3 Page:801-813
ISSN:2589-790X
Container-title:CJC Open
language:en
Short-container-title:CJC Open

Author:

Bhattacharya Moumita,Lu Dai-Yin,Ventoulis Ioannis,Greenland Gabriela V.,Yalcin Hulya,Guan Yufan,Marine Joseph E.,Olgin Jeffrey E.,Zimmerman Stefan L.,Abraham Theodore P.,Abraham M. Roselle,Shatkay Hagit

Funder

National Institutes of Health

National Science Foundation

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine

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3. Systolic blood pressure ≤110 mm Hg is associated with severe coronary microvascular ischemia and higher risk for ventricular arrhythmias in hypertrophic cardiomyopathy;Heart Rhythm O2;2023-09

4. Clinical Application of the HCM-AF Risk Score in the Prediction of Clinical Outcomes of Polish Patients with Hypertrophic Cardiomyopathy;Journal of Clinical Medicine;2023-07-04

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