Application of artificial intelligence in chronic myeloid leukemia (CML) disease prediction and management: a scoping review.

Journal: BMC cancer
PMID: 39164653

Abstract

BACKGROUND: Navigating the complexity of chronic myeloid leukemia (CML) diagnosis and management poses significant challenges, including the need for accurate prediction of disease progression and response to treatment. Artificial intelligence (AI) presents a transformative approach that enables the development of sophisticated predictive models and personalized treatment strategies that enhance early detection and improve therapeutic interventions for better patient outcomes.

Authors

  • Malihe Ram
    Faculty of Medical Sciences, Birjand university of medical sciences, Birjand, Iran.
  • Mohammad Reza Afrash
    Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Khadijeh Moulaei
    Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
  • Mohammad Parvin
    Department of Industrial and Systems Engineering, Auburn University, Auburn, AL, USA.
  • Erfan Esmaeeli
    Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Zahra Karbasi
    Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran.
  • Soroush Heydari
    Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Azam Sabahi
    Department of Health Information Technology, Ferdows faculty of Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran. sabahiazam858@gmail.com.

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