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

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

Author: 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; Schiefenhoevel, Fridtjof; Rahmel, Tim; Putensen, Christian; Sellmann, Timur; Koch, Thea; Brandenburger, Timo; Brenner, Thorsten; Berger, Marc; Zacharowski, Kai; Adam, Elisabeth; Posch, Matthias; Moerer, Onnen; Scheer, Christian S.; Sedding, Daniel; Weigand, Markus A.; Fichtner, Falk; Nau, Carla; Praetsch, 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
Tübinger Autor(en):
Magunia, Harry
Lederer, Simone
Verbuecheln, Raphael
Koeppen, Michael
Mirakaj, Valbona
Hofmann, Pascal
Kohlbacher, Oliver
Biergans, Stephanie
Rosenberger, Peter
Gilot, Bryant
Häberle, Helene
Malek, Nisar Peter
Published in: Critical Care (2021), Bd. 25, Article 295
Verlagsangabe: Bmc
Language: English
Full text: http://dx.doi.org/10.1186/s13054-021-03720-4
ISSN: 1466-609X
DDC Classifikation: 610 - Medicine and health
Dokumentart: Article
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