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Machine learning predicts the short-term requirement for invasive ventilation among Australian critically ill COVID-19 patients.

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Title: Machine learning predicts the short-term requirement for invasive ventilation among Australian critically ill COVID-19 patients.
Authors: Karri R; Royal Melbourne Hospital, Melbourne, Victoria, Australia., Chen YP; Faculty of Science, Technology and Engineering, La Trobe University, Melbourne, Victoria, Australia., Burrell AJC; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Intensive Care and Hyperbaric Medicine, The Alfred Hospital, Melbourne, Victoria, Australia., Penny-Dimri JC; Royal Melbourne Hospital, Melbourne, Victoria, Australia., Broadley T; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia., Trapani T; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia., Deane AM; Intensive Care Unit, Royal Melbourne Hospital, Melbourne, Victoria, Australia.; Department of Critical Care, Melbourne Medical School, Melbourne, Victoria, Australia., Udy AA; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Intensive Care and Hyperbaric Medicine, The Alfred Hospital, Melbourne, Victoria, Australia., Plummer MP; Intensive Care Unit, Royal Melbourne Hospital, Melbourne, Victoria, Australia.; Department of Critical Care, Melbourne Medical School, Melbourne, Victoria, Australia.
Corporate Authors: SPRINT-SARI Australia Investigators
Source: PloS one [PLoS One] 2022 Oct 26; Vol. 17 (10), pp. e0276509. Date of Electronic Publication: 2022 Oct 26 (Print Publication: 2022).
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Machine learning predicts the short-term requirement for invasive ventilation among Australian critically ill COVID-19 patients.
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  Data: <searchLink fieldCode="AU" term="%22Karri+R%22">Karri R</searchLink>; Royal Melbourne Hospital, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Chen+YP%22">Chen YP</searchLink>; Faculty of Science, Technology and Engineering, La Trobe University, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Burrell+AJC%22">Burrell AJC</searchLink>; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Intensive Care and Hyperbaric Medicine, The Alfred Hospital, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Penny-Dimri+JC%22">Penny-Dimri JC</searchLink>; Royal Melbourne Hospital, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Broadley+T%22">Broadley T</searchLink>; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Trapani+T%22">Trapani T</searchLink>; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Deane+AM%22">Deane AM</searchLink>; Intensive Care Unit, Royal Melbourne Hospital, Melbourne, Victoria, Australia.; Department of Critical Care, Melbourne Medical School, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Udy+AA%22">Udy AA</searchLink>; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Intensive Care and Hyperbaric Medicine, The Alfred Hospital, Melbourne, Victoria, Australia.<br /><searchLink fieldCode="AU" term="%22Plummer+MP%22">Plummer MP</searchLink>; Intensive Care Unit, Royal Melbourne Hospital, Melbourne, Victoria, Australia.; Department of Critical Care, Melbourne Medical School, Melbourne, Victoria, Australia.
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  Data: <searchLink fieldCode="JN" term="%22101285081%22">PloS one</searchLink> [PLoS One] 2022 Oct 26; Vol. 17 (10), pp. e0276509. <i>Date of Electronic Publication: </i>2022 Oct 26 (<i>Print Publication: </i>2022).
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