Phenotype clustering of hospitalized high-risk patients with COVID-19 — a machine learning approach within the multicentre, multinational PCHF-COVICAV registry

IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) approaches, certain phenotypes may be confined to cla...

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Hlavní autoři:	Mateusz Sokolski, Sander Trenson, Konrad Reszka, Szymon Urban, Justyna M. Sokolska, Tor Biering-Sørensen, Mats C. Højbjerg Lassen, Kristoffer Grundtvig Skaarup, Carmen Basic, Zacharias Mandalenakis, Klemens Ablasser, Peter P. Rainer, Markus Wallner, Valentina A. Rossi, Marzia Lilliu, Goran Loncar, Huseyin A. Cakmak, Frank Ruschitzka, Andreas J. Flammer
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Via Medica 2024-08-01
Edice:	Cardiology Journal
Témata:	clustering machine learning artificial intelligence COVID-19 SARS-CoV2 cardiovascular disease
On-line přístup:	https://journals.viamedica.pl/cardiology_journal/article/view/98489
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