Using machine learning models for predicting monthly iPTH levels in hemodialysis patients.

Journal: Computer methods and programs in biomedicine
PMID: 39637702

Abstract

BACKGROUND AND OBJECTIVE: Intact parathyroid hormone (iPTH), also known as active parathyroid hormone, is an important indicator commonly for monitoring secondary hyperparathyroidism (SHPT) in patients undergoing hemodialysis. The aim of this study was to use machine learning (ML) models to predict monthly iPTH levels in patients undergoing hemodialysis.

Authors

  • Chih-Chieh Hsieh
    Anhsin Health Care, Pingtung, Taiwan; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; Division of Nephrology, Department of Internal Medicine, Pingtung Christian Hospital, Pingtung, Taiwan.
  • Chin-Wen Hsieh
    Division of Nephrology, Department of Internal Medicine, Pingtung Christian Hospital, Pingtung, Taiwan.
  • Mohy Uddin
    King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Executive Office, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Kingdom of Saudi Arabia.
  • Li-Ping Hsu
    Division of Nephrology, Department of Internal Medicine, Pingtung Christian Hospital, Pingtung, Taiwan.
  • Hao-Huan Hu
    Division of Nephrology, Department of Internal Medicine, Pingtung Christian Hospital, Pingtung, Taiwan.
  • Shabbir Syed-Abdul
    Graduate Institute of Biomedical Informatics, College of Medicine Science and Technology, Taipei Medical University, Taipei, Taiwan;; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan.

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