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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Detalhes bibliográficos

Principais autores:	Robert Herman, Marc Vanderheyden, Boris Vavrik, Monika Beles, Timotej Palus, Olivier Nelis, Marc Goethals, Sofie Verstreken, Riet Dierckx, Martin Penicka, Ward Heggermont, Jozef Bartunek
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Oxford University Press 2022-10-01
coleção:	ESC Heart Failure
Assuntos:	Heart failure Machine learning Mortality prediction Risk stratification Big data analysis Precision medicine
Acesso em linha:	https://doi.org/10.1002/ehf2.14011
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