COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients

Background COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as well as limitation of clinical scoring systems have created the need for more...

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Hauptverfasser: Mamandipoor, B, Bruno, RR, Wernly, B, Wolff, G, Fjølner, J, Artigas, A, Pinto, BB, Schefold, JC, Kelm, M, Beil, M, Sigal, S, Leaver, S, De Lange, DW, Guidet, B, Flaatten, H, Szczeklik, W, Jung, C, Osmani, V
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Sprache:eng
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Zusammenfassung:Background COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as well as limitation of clinical scoring systems have created the need for more objective and consistent methods to aid clinical decision making. In this regard, machine learning methods have been shown to enhance prognostication, while improving consistency. However, current machine learning approaches have been limited by lack of generalisation to diverse patient populations, between patients admitted at different waves and small sample sizes.
DOI:10.1371/journal.pdig.0000136