Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.

Journal: BMC medical informatics and decision making
PMID: 36068539

Abstract

INTRODUCTION: Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the translocation of chromosomes 19 and 22. CML includes 15-20% of all cases of leukemia. Although bone marrow transplant and, more recently, tyrosine kinase inhibitors (TKIs) as a first-line treatment have significantly prolonged survival in CML patients, accurate prediction using available patient-level factors can be challenging. We intended to predict 5-year survival among CML patients via eight machine learning (ML) algorithms and compare their performance.

Authors

  • Mostafa Shanbehzadeh
    Department of Health Information Technology, Faculty of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
  • Mohammad Reza Afrash
    Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Nader Mirani
    Department of Treatment, Head of the Medical Truism, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Hadi Kazemi-Arpanahi
    Department of Health Information Technology, Abadan University of Medical Sciences, Abadan, Iran. H.kazemi@abadanums.ac.ir.

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