Predicting hypoglycemia in ICU patients: a machine learning approach.

Journal: Expert review of endocrinology & metabolism
PMID: 39283190

Abstract

BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast the risk of hypoglycemia among ICU patients in Jordan.

Authors

  • Reema Karasneh
    Department of Basic Medical Sciences, Faculty of Medicine, Yarmouk University, Irbid, Jordan.
  • Sayer Al-Azzam
    Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
  • Karem H Alzoubi
    Department of Pharmacy Practice and Pharmacotherapeutics, University of Sharjah, Sharjah, 27272, United Arab Emirates.
  • Muna Ebbini
    Department of Public Health and Community Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
  • Asma'a Alselwi
    Department of Public Health and Community Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
  • Dania Rahhal
    Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
  • Suad Kabbaha
    Department of Health Research Methods, Evidence & Impact (HEI), McMaster University, Hamilton, ON, Canada.
  • Mamoon A Aldeyab
    Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield, UK.
  • Aisha F Badr
    Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia.

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