{"title":"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。","authors":"Mohamed Elhadary , Amgad Mohamed Elshoeibi , Ahmed Badr , Basel Elsayed , Omar Metwally , Ahmed Mohamed Elshoeibi , Mervat Mattar , Khalil Alfarsi , Salem AlShammari , Awni Alshurafa , Mohamed Yassin","doi":"10.1016/j.blre.2023.101134","DOIUrl":null,"url":null,"abstract":"<div><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></div>","PeriodicalId":56139,"journal":{"name":"Blood Reviews","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0268960X23000954/pdfft?md5=829bc0ce581815557ac795ba350b192f&pid=1-s2.0-S0268960X23000954-main.pdf","citationCount":"1","resultStr":"{\"title\":\"Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning\",\"authors\":\"Mohamed Elhadary , Amgad Mohamed Elshoeibi , Ahmed Badr , Basel Elsayed , Omar Metwally , Ahmed Mohamed Elshoeibi , Mervat Mattar , Khalil Alfarsi , Salem AlShammari , Awni Alshurafa , Mohamed Yassin\",\"doi\":\"10.1016/j.blre.2023.101134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><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></div>\",\"PeriodicalId\":56139,\"journal\":{\"name\":\"Blood Reviews\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0268960X23000954/pdfft?md5=829bc0ce581815557ac795ba350b192f&pid=1-s2.0-S0268960X23000954-main.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Blood Reviews\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0268960X23000954\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blood Reviews","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0268960X23000954","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEMATOLOGY","Score":null,"Total":0}
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.
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.