Utilizing longitudinal data in assessing all‐cause mortality in patients hospitalized with heart failure

Utilizing longitudinal data in assessing all‐cause mortality in patients hospitalized with heart failure

Abstract Aims Risk stratification in patients with a new onset or worsened heart failure (HF) is essential for clinical decision making. We have utilized a novel approach to enrich patient level prognostication using longitudinally gathered data to develop ML‐based algorithms predicting all‐cause 30...

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Bibliographic Details
Main Authors: Robert Herman, Marc Vanderheyden, Boris Vavrik, Monika Beles, Timotej Palus, Olivier Nelis, Marc Goethals, Sofie Verstreken, Riet Dierckx, Martin Penicka, Ward Heggermont, Jozef Bartunek
Format: Article
Language:English
Published: Wiley 2022-10-01
Series:ESC Heart Failure
Subjects:
Heart failure
Machine learning
Mortality prediction
Risk stratification
Big data analysis
Precision medicine
Online Access:https://doi.org/10.1002/ehf2.14011

Internet

https://doi.org/10.1002/ehf2.14011

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