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pro vyhledávání: '"Aaron W. Sievering"'
Autor:
Aaron W. Sievering, Peter Wohlmuth, Nele Geßler, Melanie A. Gunawardene, Klaus Herrlinger, Berthold Bein, Dirk Arnold, Martin Bergmann, Lorenz Nowak, Christian Gloeckner, Ina Koch, Martin Bachmann, Christoph U. Herborn, Axel Stang
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-14 (2022)
Abstract Background Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with stati
Externí odkaz:
https://doaj.org/article/faf7bce8af36413089cdfd88cfc2965c
