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

Harry Magunia*, Simone Lederer, Raphael Verbuecheln, Bryant Joseph Gilot, Michael Koeppen, Helene A. Haeberle, Valbona Mirakaj, Pascal Hofmann, Gernot Marx, Johannes Bickenbach, Boris Nohe, Michael Lay, Claudia Spies, Andreas Edel, Fridtjof Schiefenhövel, Tim Rahmel, Christian Putensen, Timur Sellmann, Thea Koch, Timo BrandenburgerDetlef Kindgen-Milles, Thorsten Brenner, Marc Berger, Kai Zacharowski, Elisabeth Adam, Matthias Posch, Onnen Moerer, Christian S. Scheer, Daniel Sedding, Markus A. Weigand, Falk Fichtner, Carla Nau, Florian Prätsch, Thomas Wiesmann, Christian Koch, Gerhard Schneider, Tobias Lahmer, Andreas Straub, Andreas Meiser, Manfred Weiss, Bettina Jungwirth, Frank Wappler, Patrick Meybohm, Johannes Herrmann, Nisar Malek, Oliver Kohlbacher, Stephanie Biergans, Peter Rosenberger

*Corresponding author for this work
15 Citations (Scopus)

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Nursing and Health Professions

Pharmacology, Toxicology and Pharmaceutical Science

Medicine and Dentistry

Biochemistry, Genetics and Molecular Biology