Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort
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Autores:
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 Brandenburger, Detlef Kindgen-Milles, Thorsten Brenner, Marc Berger, Kai Zacharo
Publicado en:
Critical Care, Edición 295 (2021), 2021, Página(s) 25, ISSN 1364-8535
Editor:
BMC
DOI:
10.1186/s13054-021-03720-4
ENVISION – Improve intensive care of COVID-19 patients with artificial intelligence
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Autores:
Alpo Olavi Värri, Antti Kallonen, Hannu Nieminen, Mark Van Gils
Publicado en:
Finnish Journal of EHealth and EWelfare, Edición 13 (4), 2021, Página(s) 449-453, ISSN 1798-0798
Editor:
Finnish Social and Health Informatics Association
DOI:
10.23996/fjhw.109929
Additional file 1 of Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort
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Autores:
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; Be
Publicado en:
Springer Nature, 2021, ISSN 1364-8535
Editor:
BMC
DOI:
10.6084/m9.figshare.15184814