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Article

A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity.

JACC. Cardiovascular imaging - 1 Sept 2021

Sengupta Partho P, Shrestha Sirish, Kagiyama Nobuyuki, Hamirani Yasmin, Kulkarni Hemant, Yanamala Naveena, Bing Rong, Chin Calvin W L, Pawade Tania A, Messika-Zeitoun David, Tastet Lionel, Shen Mylène, Newby David E, Clavel Marie-Annick, Pibarot Phillippe, Dweck Marc R

Abstract excerpt

OBJECTIVES: The authors explored the development and validation of machine-learning models for augmenting the echocardiographic grading of aortic stenosis (AS) severity. BACKGROUND: In AS, symptoms and adverse events develop secondarily to valvular obstruction and left ventricular decompensation. The current echocardiographic grading of AS severity focuses on the valve and is limited by diagnostic uncertainty....

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 34023273
DOI: 10.1016/j.jcmg.2021.03.020
PMCID: PMC8434951

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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