Predicting hypoglycemia in ICU patients: a machine learning approach

Author:

Karasneh Reema1,Al-Azzam Sayer2,Alzoubi Karem H.34,Ebbini Muna5,Alselwi Asma’a5,Rahhal Dania2,Kabbaha Suad6,Aldeyab Mamoon A7ORCID,Badr Aisha F.8

Affiliation:

1. Department of Basic Medical Sciences, Faculty of Medicine, Yarmouk University, Irbid, Jordan

2. Department of Clinical Pharmacy, Jordan University of Science and Technology, Irbid, Jordan

3. Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy University of Sharjah, Sharjah, United Arab Emirates

4. Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan

5. Department of Public Health and Community Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan

6. Department of Health Research Methods, Evidence & Impact (HEI), McMaster University, Hamilton, ON, Canada

7. Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield, UK

8. Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia

Publisher

Informa UK Limited

Reference38 articles.

1. Revisiting tight glycemic control in perioperative and critically ill patients: when one size may not fit all

2. San PP, Ling SH, Soe NN, et al., editors. A novel extreme learning machine for hypoglycemia detection. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2014: IEEE.

3. Hypoglycemia during therapy of diabetes;Davis HA;Endotext,2021

4. Glycemic targets: standards of medical care in diabetes—2022;American Diabetes Association;Diabetes care

5. Predicting hypoglycemia in critically Ill patients using machine learning and electronic health records;Mantena S;J Clin Monit Comput,2021

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