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Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.
Cheng, Zhangkai J; Li, Haiyang; Liu, Mingtao; Fu, Xing; Liu, Li; Liang, Zhiman; Gan, Hui; Sun, Baoqing.
Afiliación
  • Cheng ZJ; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Li H; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Liu M; MRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK. haiyang.li@mrc-bsu.cam.ac.uk.
  • Fu X; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Liu L; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Liang Z; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Gan H; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
  • Sun B; Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 51
BMC Cancer ; 24(1): 993, 2024 Aug 12.
Article en En | MEDLINE | ID: mdl-39134989
ABSTRACT
Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute leukemia. This study aimed to develop an early and comprehensive predictor for hematologic malignancies in children by analyzing nutritional biomarkers, key leukemia indicators, and granulocytes in their blood. Using a machine learning algorithm and ten indices, the blood samples of 826 children with ALL and 255 children with AML were compared to a control group of 200 healthy children. The study revealed notable differences, including higher indicators in boys compared to girls and significant variations in most biochemical indicators between leukemia patients and healthy children. Employing a random forest model resulted in an area under the curve (AUC) of 0.950 for predicting leukemia subtypes and an AUC of 0.909 for forecasting AML. This research introduces an efficient diagnostic tool for early screening of childhood blood cancers and underscores the potential of artificial intelligence in modern healthcare.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Leucemia Mieloide Aguda / Leucemia-Linfoma Linfoblástico de Células Precursoras Límite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: BMC Cancer Asunto de la revista: NEOPLASIAS Año: 2024 Tipo del documento: Article
Texto completo
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Leucemia Mieloide Aguda / Leucemia-Linfoma Linfoblástico de Células Precursoras Límite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: BMC Cancer Asunto de la revista: NEOPLASIAS Año: 2024 Tipo del documento: Article