Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation follow...
Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach
About this item
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Author / Creator
Li, Zhenzhen , Fan, Jianing , Fan, Jiajun , Miao, Jiaxin , Lin, Dawei , Zhao, Jingyan , Zhang, Xiaochun , Pan, Wenzhi , Zhou, Daxin and Ge, Junbo
Publisher
England: BioMed Central Ltd
Journal title
Language
English
Formats
Publication information
Publisher
England: BioMed Central Ltd
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Scope and Contents
Contents
Post-operative moderate-to-severe mitral regurgitation (MR) following transcatheter aortic valve replacement (TAVR) is associated with poor outcomes, yet the factors contributing to this complication are not well understood. This study aimed to identify risk factors and develop predictive models for post-operative MR following TAVR using machine le...
Alternative Titles
Full title
Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach
Authors, Artists and Contributors
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_b89693a805e94c77bce05e5d9d0091ec
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b89693a805e94c77bce05e5d9d0091ec
Other Identifiers
ISSN
1471-2261
E-ISSN
1471-2261
DOI
10.1186/s12872-025-04759-9
