革命性的慢性淋巴细胞白血病诊断:深入研究机器学习的各种应用。

IF 6.9 2区 医学 Q1 HEMATOLOGY
Mohamed Elhadary , Amgad Mohamed Elshoeibi , Ahmed Badr , Basel Elsayed , Omar Metwally , Ahmed Mohamed Elshoeibi , Mervat Mattar , Khalil Alfarsi , Salem AlShammari , Awni Alshurafa , Mohamed Yassin
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引用次数: 1

摘要

慢性淋巴细胞白血病(CLL)是一种以异常单克隆B淋巴细胞积聚为特征的B细胞肿瘤。CLL是西方国家主要的白血病类型,占病例的25%。尽管许多患者仍然没有症状,但一部分患者可能表现出典型的淋巴瘤症状、获得性免疫缺陷障碍或自身免疫性并发症。诊断包括血液测试显示淋巴细胞增加,并使用外周血涂片和流式细胞术进行进一步检查以确认疾病。近年来,随着机器学习(ML)和人工智能(AI)的显著进步,已经提出了许多模型和算法来支持CLL的诊断和分类。在这篇综述中,我们讨论了ML算法在诊断和评估CLL患者中的最新应用的优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning

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.

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来源期刊
Blood Reviews
Blood Reviews 医学-血液学
CiteScore
13.80
自引率
1.40%
发文量
78
期刊介绍: Blood Reviews, a highly regarded international journal, serves as a vital information hub, offering comprehensive evaluations of clinical practices and research insights from esteemed experts. Specially commissioned, peer-reviewed articles authored by leading researchers and practitioners ensure extensive global coverage across all sub-specialties of hematology.
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