Early prediction of circulatory failure in the intensive care unit using machine learning.
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| Title: | Early prediction of circulatory failure in the intensive care unit using machine learning. |
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| Authors: | Hyland SL; Department of Computer Science, ETH Zürich, Zürich, Switzerland.; Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.; Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA.; Medical Informatics Unit, Zürich University Hospital, Zürich, Switzerland., Faltys M; Department of Intensive Care Medicine, University Hospital, University of Bern, Bern, Switzerland., Hüser M; Department of Computer Science, ETH Zürich, Zürich, Switzerland.; Medical Informatics Unit, Zürich University Hospital, Zürich, Switzerland., Lyu X; Department of Computer Science, ETH Zürich, Zürich, Switzerland.; Medical Informatics Unit, Zürich University Hospital, Zürich, Switzerland., Gumbsch T; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Esteban C; Department of Computer Science, ETH Zürich, Zürich, Switzerland.; Medical Informatics Unit, Zürich University Hospital, Zürich, Switzerland., Bock C; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Horn M; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Moor M; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Rieck B; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Zimmermann M; Department of Computer Science, ETH Zürich, Zürich, Switzerland., Bodenham D; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.; Swiss Institute for Bioinformatics, Lausanne, Switzerland., Borgwardt K; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland. karsten.borgwardt@bsse.ethz.ch.; Swiss Institute for Bioinformatics, Lausanne, Switzerland. karsten.borgwardt@bsse.ethz.ch., Rätsch G; Department of Computer Science, ETH Zürich, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch.; Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. gunnar.raetsch@inf.ethz.ch.; Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA. gunnar.raetsch@inf.ethz.ch.; Medical Informatics Unit, Zürich University Hospital, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch.; Swiss Institute for Bioinformatics, Lausanne, Switzerland. gunnar.raetsch@inf.ethz.ch.; Department of Biology, ETH Zürich, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch., Merz TM; Department of Intensive Care Medicine, University Hospital, University of Bern, Bern, Switzerland. tobiasm@adhb.govt.nz.; Cardiovascular Intensive Care Unit, Auckland City Hospital, Auckland, New Zealand. tobiasm@adhb.govt.nz. |
| Source: | Nature medicine [Nat Med] 2020 Mar; Vol. 26 (3), pp. 364-373. Date of Electronic Publication: 2020 Mar 09. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Publishing Company Country of Publication: United States NLM ID: 9502015 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-170X (Electronic) Linking ISSN: 10788956 NLM ISO Abbreviation: Nat Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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