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Article

Unsupervised machine learning to identify subphenotypes among cardiac intensive care unit patients with heart failure.

ESC heart failure - 1 Dec 2024

Jentzer Jacob C, Reddy Yogesh N V, Soussi Sabri, Crespo-Diaz Ruben, Patel Parag C, Lawler Patrick R, Mebazaa Alexandre, Dunlay Shannon M

Abstract excerpt

AIMS: Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac intensive care unit (CICU). We aimed to leverage unsupervised machine learning to identify previously unknown HF phenotypes in a large and diverse cohort of patients...

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Follow-Up Studies
Heart Failure
Hospital Mortality
Intensive Care Units

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Unsupervised Machine Learning

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PMID: 39160644
DOI: 10.1002/ehf2.15027
PMCID: PMC11631334

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