Machine learning for initial insulin estimation in hospitalized patients.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 34279615

Abstract

OBJECTIVE: The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic health records more accurately than existing guideline-based dosing recommendations.

Authors

  • Minh Nguyen
    Clinical Imaging Research Centre, Centre for Sleep and Cognition, N.1 Institute for Health and Memory Networks Program, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore.
  • Ivana Jankovic
    Division of Endocrinology, Department of Medicine, Stanford University, School of Medicine, Stanford, California, USA.
  • Laurynas Kalesinskas
    Department of Biomedical Data Science, Stanford University, School of Medicine, Stanford, California, USA.
  • Michael Baiocchi
    Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA.
  • Jonathan H Chen
    Stanford Center for Biomedical Informatics Research, Stanford, CA.

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