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10.1016_j.blre.2023.101134.pdf (5.75 MB)

Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning

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submitted on 2023-11-22, 09:49 and posted on 2023-11-22, 11:34 authored by Mohamed Elhadary, Amgad Mohamed Elshoeibi, Ahmed Badr, Basel Elsayed, Omar Metwally, Ahmed Mohamed Elshoeibi, Mervat Mattar, Khalil Alfarsi, Salem AlShammari, Awni Alshurafa, Mohamed Yassin

Chronic lymphocytic leukemia (CLL) is a B cell neoplasm characterized by the accumulation of aberrant monoclonal B lymphocytes. CLL is the predominant type of leukemia in Western countries, accounting for 25% of cases. Although many patients remain asymptomatic, a subset may exhibit typical lymphoma symptoms, acquired immunodeficiency disorders, or autoimmune complications. Diagnosis involves blood tests showing increased lymphocytes and further examination using peripheral blood smear and flow cytometry to confirm the disease. With the significant advancements in machine learning (ML) and artificial intelligence (AI) in recent years, numerous models and algorithms have been proposed to support the diagnosis and classification of CLL. In this review, we discuss the benefits and drawbacks of recent applications of ML algorithms in the diagnosis and evaluation of patients diagnosed with CLL.

Other Information

Published in: Blood Reviews
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.blre.2023.101134

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Qatar University
  • Qatar University Health - QU
  • College of Medicine - QU HEALTH
  • Hamad Medical Corporation
  • National Center for Cancer Care and Research - HMC