Towards Diagnostic Intelligent Systems in Leukemia Detection and Classification: A Systematic Review and Meta-analysis.

Journal: Journal of evidence-based medicine
PMID: 40013326

Abstract

OBJECTIVE: Leukemia is a type of blood cancer that begins in the bone marrow and results in high numbers of abnormal white blood cells. Automated detection and classification of leukemia and its subtypes using artificial intelligence (AI) and machine learning (ML) algorithms plays a significant role in the early diagnosis and treatment of this fatal disease. This study aimed to review and synthesize research findings on AI-based approaches in leukemia detection and classification from peripheral blood smear images.

Authors

  • Mehrad Aria
    Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Zohreh Javanmard
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Donia Pishdad
    Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.
  • Vahid Jannesari
    Department of Industrial, Systems, and Manufacturing Engineering (ISME), Wichita State University, Wichita, Kansas, USA.
  • Maryam Keshvari
    Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, Kansas, USA.
  • Mahshid Arastonejad
    Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, USA.
  • Reza Safdari
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: rsafdari@tums.ac.ir.
  • Mohammad Esmaeil Akbari
    Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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