Machine learning-aided risk stratification in Philadelphia chromosome-positive acute lymphoblastic leukemia

Machine learning-aided risk stratification in Philadelphia chromosome-positive acute lymphoblastic leukemia

Abstract We used the eXtreme Gradient Boosting algorithm, an optimized gradient boosting machine learning library, and established a model to predict events in Philadelphia chromosome-positive acute lymphoblastic leukemia using a machine learning-aided method. A model was constructed using a trainin...

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Bibliographic Details
Main Authors: Satoshi Nishiwaki, Isamu Sugiura, Daisuke Koyama, Yukiyasu Ozawa, Masahide Osaki, Yuichi Ishikawa, Hitoshi Kiyoi
Format: Article
Language:English
Published: BMC 2021-02-01
Series:Biomarker Research
Subjects:
eXtreme gradient boosting algorithm
Machine learning
Philadelphia chromosome-positive acute lymphoblastic leukemia
Prognostic factor
Survival stratification
Online Access:https://doi.org/10.1186/s40364-021-00268-x

Internet

https://doi.org/10.1186/s40364-021-00268-x

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