Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospec...

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Detalles Bibliográficos
Autores principales: Magunia, Harry, Lederer, Simone, Verbuecheln, Raphael, Gilot, Bryant Joseph, Koeppen, Michael, Haeberle, Helene A., Mirakaj, Valbona, Hofmann, Pascal, Marx, Gernot, Bickenbach, Johannes, Nohe, Boris, Lay, Michael, Spies, Claudia, Edel, Andreas, Schiefenhövel, Fridtjof, Rahmel, Tim, Putensen, Christian, Sellmann, Timur, Koch, Thea, Brandenburger, Timo, Kindgen-Milles, Detlef, Brenner, Thorsten, Berger, Marc, Zacharowski, Kai, Adam, Elisabeth, Posch, Matthias, Moerer, Onnen, Scheer, Christian S., Sedding, Daniel, Weigand, Markus A., Fichtner, Falk, Nau, Carla, Prätsch, Florian, Wiesmann, Thomas, Koch, Christian, Schneider, Gerhard, Lahmer, Tobias, Straub, Andreas, Meiser, Andreas, Weiss, Manfred, Jungwirth, Bettina, Wappler, Frank, Meybohm, Patrick, Herrmann, Johannes, Malek, Nisar, Kohlbacher, Oliver, Biergans, Stephanie, Rosenberger, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8370055/
https://www.ncbi.nlm.nih.gov/pubmed/34404458
http://dx.doi.org/10.1186/s13054-021-03720-4

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