Prediction of tumor lysis syndrome in childhood acute lymphoblastic leukemia based on machine learning models: a retrospective study

Prediction of tumor lysis syndrome in childhood acute lymphoblastic leukemia based on machine learning models: a retrospective study

BackgroundTumor lysis syndrome (TLS) often occurs early after induction chemotherapy for acute lymphoblastic leukemia (ALL) and can rapidly progress. This study aimed to construct a machine learning model to predict the risk of TLS using clinical indicators at the time of ALL diagnosis.MethodsThis o...

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Bibliographic Details
Main Authors: Yao Xiao, Li Xiao, Yang Zhang, Ximing Xu, Xianmin Guan, Yuxia Guo, Yali Shen, XiaoYing Lei, Ying Dou, Jie Yu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-03-01
Series:Frontiers in Oncology
Subjects:
machine learning
predictive modeling
acute lymphoblastic leukemia
tumor lysis syndrome
treatment toxicity
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2024.1337295/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2024.1337295/full

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