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Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aor...

Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aor...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cc4bd72af53244d6ae7ba01960c41942

Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aortic Stenosis Patients

About this item

Full title

Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aortic Stenosis Patients

Publisher

Switzerland: MDPI AG

Journal title

Medical sciences (Basel), 2023-12, Vol.12 (1), p.3

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

The current recommendation for bioprosthetic valve replacement in severe aortic stenosis (AS) is either surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR). We evaluated the performance of a machine learning-based predictive model using existing periprocedural variables for valve replacement modality selection....

Alternative Titles

Full title

Machine Learning-Based Predictive Model of Aortic Valve Replacement Modality Selection in Severe Aortic Stenosis Patients

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_cc4bd72af53244d6ae7ba01960c41942

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cc4bd72af53244d6ae7ba01960c41942

Other Identifiers

ISSN

2076-3271

E-ISSN

2076-3271

DOI

10.3390/medsci12010003

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