An Automated Machine Learning–Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading-Reference-Cited by-同舟云学术

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An Automated Machine Learning–Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading

Published:2024-08 Issue: Volume: Page:
ISSN:1936-878X
Container-title:JACC: Cardiovascular Imaging
language:en
Short-container-title:JACC: Cardiovascular Imaging

Author:

Sadeghpour Anita,Jiang Zhubo,Hummel Yoran M.,Frost Matthew,Lam Carolyn S.P.,Shah Sanjiv J.,Lund Lars H.,Stone Gregg W.,Swaminathan Madhav,Weissman Neil J.,Asch Federico M.

Publisher

Elsevier BV

Reference30 articles.

1. Burden of valvular heart diseases: a population-based study;Nkomo;Lancet,2006

2. 2020 focused update of the 2017 ACC Expert Consensus Decision Pathway on the Management of Mitral Regurgitation;Bonow;J Am Coll Cardiol,2020

3. Contemporary presentation and management of valvular heart disease;Iung;Circulation,2019

4. Percutaneous repair or surgery for mitral regurgitation;Feldman;N Engl J Med,2011

5. Transcatheter mitral-valve repair in patients with heart failure;Stone;N Engl J Med,2018

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