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Article

Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.

JACC. Cardiovascular imaging - 1 May 2025

Malahfji Maan, Tan Xin, Kaolawanich Yodying, Saeed Mujtaba, Guta Andrada, Reardon Michael J, Zoghbi William A, Polsani Venkateshwar, Elliott Michael, Kim Raymond, Li Meng, Shah Dipan J

Abstract excerpt

BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically. OBJECTIVES: The aim of this study was to first use unsupervised machine learning to identify unique patient phenoclusters in AR, and subsequently evaluate their prognostic relevance. METHODS: Clinical and cardiac magnetic...

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Machine Learning
Aortic Valve
Decision Support Techniques
Magnetic Resonance Imaging, Cine
Predictive Value of Tests

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Unsupervised Machine Learning

Ventricular Function, Left

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Identifiers

PMID: 40146099
DOI: 10.1016/j.jcmg.2025.01.006
PMCID: PMC12058414

Genes

AR

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

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