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

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

Abstract 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 lev...

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Bibliographic Details
Main Authors: Jacob C. Jentzer, Yogesh N.V. Reddy, Sabri Soussi, Ruben Crespo‐Diaz, Parag C. Patel, Patrick R. Lawler, Alexandre Mebazaa, Shannon M. Dunlay
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:ESC Heart Failure
Subjects:
cardiac intensive care unit
cardiogenic shock
heart failure
machine learning
mortality
phenotyping
Online Access:https://doi.org/10.1002/ehf2.15027
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https://doi.org/10.1002/ehf2.15027

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