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Machine learning to predict in-hospital mortality among patients with severe obesity: Proof of concept study.

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Title: Machine learning to predict in-hospital mortality among patients with severe obesity: Proof of concept study.
Authors: Soffer S; Internal Medicine B Assuta Medical Center Ashdod Israel.; Ben-Gurion University of the Negev Be'er Sheva Israel., Zimlichman E; Hospital Management Sheba Medical Center Tel Hashomer Israel.; Sackler Medical School Tel Aviv University Tel Aviv Israel.; Sheba Talpiot Medical Leadership Program Tel Hashomer Israel., Levin MA; Department of Population Health Science and Policy Institute for Healthcare Delivery Science Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Anesthesiology, Perioperative and Pain Medicine Icahn School of Medicine at Mount Sinai New York New York USA., Zebrowski AM; Department of Emergency Medicine Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Population Health Science and Policy Institute for Translational Epidemiology Icahn School of Medicine at Mount Sinai New York New York USA., Glicksberg BS; Hasso Plattner Institute for Digital Health at Mount Sinai Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York New York USA., Freeman R; Department of Population Health Science and Policy Institute for Healthcare Delivery Science Icahn School of Medicine at Mount Sinai New York New York USA., Reich DL; Department of Anesthesiology, Perioperative and Pain Medicine Icahn School of Medicine at Mount Sinai New York New York USA., Klang E; Sackler Medical School Tel Aviv University Tel Aviv Israel.; Sheba Talpiot Medical Leadership Program Tel Hashomer Israel.; Department of Diagnostic Imaging Sheba Medical Center Tel Hashomer Israel.
Source: Obesity science & practice [Obes Sci Pract] 2022 Mar 24; Vol. 8 (4), pp. 474-482. Date of Electronic Publication: 2022 Mar 24 (Print Publication: 2022).
Publication Type: Journal Article
Journal Info: Publisher: John Wiley & Sons Inc Country of Publication: United States NLM ID: 101675151 Publication Model: eCollection Cited Medium: Internet ISSN: 2055-2238 (Electronic) Linking ISSN: 20552238 NLM ISO Abbreviation: Obes Sci Pract Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Machine learning to predict in-hospital mortality among patients with severe obesity: Proof of concept study.
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  Data: <searchLink fieldCode="AU" term="%22Soffer+S%22">Soffer S</searchLink>; Internal Medicine B Assuta Medical Center Ashdod Israel.; Ben-Gurion University of the Negev Be'er Sheva Israel.<br /><searchLink fieldCode="AU" term="%22Zimlichman+E%22">Zimlichman E</searchLink>; Hospital Management Sheba Medical Center Tel Hashomer Israel.; Sackler Medical School Tel Aviv University Tel Aviv Israel.; Sheba Talpiot Medical Leadership Program Tel Hashomer Israel.<br /><searchLink fieldCode="AU" term="%22Levin+MA%22">Levin MA</searchLink>; Department of Population Health Science and Policy Institute for Healthcare Delivery Science Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Anesthesiology, Perioperative and Pain Medicine Icahn School of Medicine at Mount Sinai New York New York USA.<br /><searchLink fieldCode="AU" term="%22Zebrowski+AM%22">Zebrowski AM</searchLink>; Department of Emergency Medicine Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Population Health Science and Policy Institute for Translational Epidemiology Icahn School of Medicine at Mount Sinai New York New York USA.<br /><searchLink fieldCode="AU" term="%22Glicksberg+BS%22">Glicksberg BS</searchLink>; Hasso Plattner Institute for Digital Health at Mount Sinai Icahn School of Medicine at Mount Sinai New York New York USA.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York New York USA.<br /><searchLink fieldCode="AU" term="%22Freeman+R%22">Freeman R</searchLink>; Department of Population Health Science and Policy Institute for Healthcare Delivery Science Icahn School of Medicine at Mount Sinai New York New York USA.<br /><searchLink fieldCode="AU" term="%22Reich+DL%22">Reich DL</searchLink>; Department of Anesthesiology, Perioperative and Pain Medicine Icahn School of Medicine at Mount Sinai New York New York USA.<br /><searchLink fieldCode="AU" term="%22Klang+E%22">Klang E</searchLink>; Sackler Medical School Tel Aviv University Tel Aviv Israel.; Sheba Talpiot Medical Leadership Program Tel Hashomer Israel.; Department of Diagnostic Imaging Sheba Medical Center Tel Hashomer Israel.
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  Data: <searchLink fieldCode="JN" term="%22101675151%22">Obesity science & practice</searchLink> [Obes Sci Pract] 2022 Mar 24; Vol. 8 (4), pp. 474-482. <i>Date of Electronic Publication: </i>2022 Mar 24 (<i>Print Publication: </i>2022).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22John+Wiley+%26+Sons+Inc%22">John Wiley & Sons Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101675151 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2055-2238 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220552238%22">20552238 </searchLink><i>NLM ISO Abbreviation: </i>Obes Sci Pract <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1002/osp4.571
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        Text: English
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              Text: 2022 Mar 24
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