Prognostic Features for Overall Survival in Male Diabetic Patients Undergoing Hemodialysis Using Elastic Net Penalized Cox Regression; A Machine Learning Approach.

Journal: Archives of Iranian medicine
PMID: 40001324

Abstract

BACKGROUND: Diabetics constitute a significant percentage of hemodialysis (HD) patients with higher mortality, especially among male patients. A machine learning algorithm was used to optimize the prediction of time to death in male diabetic hemodialysis (MDHD) patients.

Authors

  • Mehrdad Sharifi
    Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Emergency Medicine Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Razieh Sadat Mousavi-Roknabadi
    Health System Research, Vice-Chancellor of Treatment, Shiraz University of Medical Sciences, Shiraz, Iran Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Vahid Ebrahimi
    CREOL, The College of Optics and Photonics, University of Central Florida, Orlando, FL, USA.
  • Robab Sadegh
    Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Emergency Medicine Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Afsaneh Dehbozorgi
    Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Emergency Medicine Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Seyed Rouhollah Hosseini-Marvast
    Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Emergency Medicine Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Mojtaba Mokdad
    Gomel State Medical University, Gomel, Belarus.

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