Phenotyping valvular heart diseases using the lens of unsupervised machine learning: a scoping review

Abstract As the population ages, the incidence and mortality of valvular heart disease (VHD) are rising. Current diagnostic approaches depend on expert heuristics, which may miss complex phenotypes. Unsupervised machine learning (ML) offers a scalable, data-driven alternative capable of identifying...

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Bibliographic Details

Published in:	npj Cardiovascular Health
Main Authors:	Max Rosen, Karthik Seetharam, Pamela Panahon, Naveena Yanamala, Partho P. Sengupta, Yasmin S. Hamirani
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-09-01
Online Access:	https://doi.org/10.1038/s44325-025-00077-3