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

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Bibliographic Details
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
Description
ISSN:1935-5548
DOI:10.2337/dc19-1743