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

<p>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...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mohamed Elhadary (16329082) (author)
مؤلفون آخرون: Amgad Mohamed Elshoeibi (17430963) (author), Ahmed Badr (16238297) (author), Basel Elsayed (14614273) (author), Omar Metwally (17430966) (author), Ahmed Mohamed Elshoeibi (17430969) (author), Mervat Mattar (17430972) (author), Khalil Alfarsi (17430975) (author), Salem AlShammari (17430978) (author), Awni Alshurafa (15468195) (author), Mohamed Yassin (4166515) (author)
منشور في: 2023
الموضوعات:
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author Mohamed Elhadary (16329082)
author2 Amgad Mohamed Elshoeibi (17430963)
Ahmed Badr (16238297)
Basel Elsayed (14614273)
Omar Metwally (17430966)
Ahmed Mohamed Elshoeibi (17430969)
Mervat Mattar (17430972)
Khalil Alfarsi (17430975)
Salem AlShammari (17430978)
Awni Alshurafa (15468195)
Mohamed Yassin (4166515)
author2_role author
author
author
author
author
author
author
author
author
author
author_facet Mohamed Elhadary (16329082)
Amgad Mohamed Elshoeibi (17430963)
Ahmed Badr (16238297)
Basel Elsayed (14614273)
Omar Metwally (17430966)
Ahmed Mohamed Elshoeibi (17430969)
Mervat Mattar (17430972)
Khalil Alfarsi (17430975)
Salem AlShammari (17430978)
Awni Alshurafa (15468195)
Mohamed Yassin (4166515)
author_role author
dc.creator.none.fl_str_mv Mohamed Elhadary (16329082)
Amgad Mohamed Elshoeibi (17430963)
Ahmed Badr (16238297)
Basel Elsayed (14614273)
Omar Metwally (17430966)
Ahmed Mohamed Elshoeibi (17430969)
Mervat Mattar (17430972)
Khalil Alfarsi (17430975)
Salem AlShammari (17430978)
Awni Alshurafa (15468195)
Mohamed Yassin (4166515)
dc.date.none.fl_str_mv 2023-09-22T06:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.blre.2023.101134
dc.relation.none.fl_str_mv https://figshare.com/articles/preprint/Revolutionizing_chronic_lymphocytic_leukemia_diagnosis_A_deep_dive_into_the_diverse_applications_of_machine_learning/24607302
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biomedical and clinical sciences
Cardiovascular medicine and haematology
Oncology and carcinogenesis
Information and computing sciences
Artificial intelligence
Machine learning
Artificial intelligence
Chronic lymphocytic leukemia
Diagnosis
Machine learning
dc.title.none.fl_str_mv Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
dc.type.none.fl_str_mv Text
Preprint
info:eu-repo/semantics/publishedVersion
text
preprint
description <p>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.</p><h2>Other Information</h2> <p> Published in: Blood Reviews<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.blre.2023.101134" target="_blank">https://dx.doi.org/10.1016/j.blre.2023.101134</a></p>
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identifier_str_mv 10.1016/j.blre.2023.101134
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/24607302
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spelling Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learningMohamed Elhadary (16329082)Amgad Mohamed Elshoeibi (17430963)Ahmed Badr (16238297)Basel Elsayed (14614273)Omar Metwally (17430966)Ahmed Mohamed Elshoeibi (17430969)Mervat Mattar (17430972)Khalil Alfarsi (17430975)Salem AlShammari (17430978)Awni Alshurafa (15468195)Mohamed Yassin (4166515)Biomedical and clinical sciencesCardiovascular medicine and haematologyOncology and carcinogenesisInformation and computing sciencesArtificial intelligenceMachine learningArtificial intelligenceChronic lymphocytic leukemiaDiagnosisMachine learning<p>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.</p><h2>Other Information</h2> <p> Published in: Blood Reviews<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.blre.2023.101134" target="_blank">https://dx.doi.org/10.1016/j.blre.2023.101134</a></p>2023-09-22T06:00:00ZTextPreprintinfo:eu-repo/semantics/publishedVersiontextpreprint10.1016/j.blre.2023.101134https://figshare.com/articles/preprint/Revolutionizing_chronic_lymphocytic_leukemia_diagnosis_A_deep_dive_into_the_diverse_applications_of_machine_learning/24607302CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/246073022023-09-22T06:00:00Z
spellingShingle Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
Mohamed Elhadary (16329082)
Biomedical and clinical sciences
Cardiovascular medicine and haematology
Oncology and carcinogenesis
Information and computing sciences
Artificial intelligence
Machine learning
Artificial intelligence
Chronic lymphocytic leukemia
Diagnosis
Machine learning
status_str publishedVersion
title Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
title_full Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
title_fullStr Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
title_full_unstemmed Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
title_short Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
title_sort Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
topic Biomedical and clinical sciences
Cardiovascular medicine and haematology
Oncology and carcinogenesis
Information and computing sciences
Artificial intelligence
Machine learning
Artificial intelligence
Chronic lymphocytic leukemia
Diagnosis
Machine learning