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Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records.

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Title: Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records.
Authors: Ruan Y; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K., Bellot A; Department of Mathematics, University of Cambridge, Cambridge, U.K.; Alan Turing Institute, London, U.K., Moysova Z; Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K., Tan GD; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K., Lumb A; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K., Davies J; Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K., van der Schaar M; Department of Mathematics, University of Cambridge, Cambridge, U.K.; Alan Turing Institute, London, U.K., Rea R; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K. rustam.rea@nhs.net.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.
Source: Diabetes care [Diabetes Care] 2020 Jul; Vol. 43 (7), pp. 1504-1511. Date of Electronic Publication: 2020 Apr 29.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: American Diabetes Association Country of Publication: United States NLM ID: 7805975 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1935-5548 (Electronic) Linking ISSN: 01495992 NLM ISO Abbreviation: Diabetes Care Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Ruan+Y%22">Ruan Y</searchLink>; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K.<br /><searchLink fieldCode="AU" term="%22Bellot+A%22">Bellot A</searchLink>; Department of Mathematics, University of Cambridge, Cambridge, U.K.; Alan Turing Institute, London, U.K.<br /><searchLink fieldCode="AU" term="%22Moysova+Z%22">Moysova Z</searchLink>; Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K.<br /><searchLink fieldCode="AU" term="%22Tan+GD%22">Tan GD</searchLink>; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.<br /><searchLink fieldCode="AU" term="%22Lumb+A%22">Lumb A</searchLink>; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.<br /><searchLink fieldCode="AU" term="%22Davies+J%22">Davies J</searchLink>; Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K.<br /><searchLink fieldCode="AU" term="%22van+der+Schaar+M%22">van der Schaar M</searchLink>; Department of Mathematics, University of Cambridge, Cambridge, U.K.; Alan Turing Institute, London, U.K.<br /><searchLink fieldCode="AU" term="%22Rea+R%22">Rea R</searchLink>; Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K. rustam.rea@nhs.net.; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22American+Diabetes+Association%22">American Diabetes Association </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>7805975 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1935-5548 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2201495992%22">01495992 </searchLink><i>NLM ISO Abbreviation: </i>Diabetes Care <i>Subsets: </i>MEDLINE
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        Value: 10.2337/dc19-1743
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              Text: 2020 Jul
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