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

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 training set (80...

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Detalles Bibliográficos
Autores principales: Nishiwaki, Satoshi, Sugiura, Isamu, Koyama, Daisuke, Ozawa, Yukiyasu, Osaki, Masahide, Ishikawa, Yuichi, Kiyoi, Hitoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Letter to the Editor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890949/
https://www.ncbi.nlm.nih.gov/pubmed/33602341
http://dx.doi.org/10.1186/s40364-021-00268-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890949/
https://www.ncbi.nlm.nih.gov/pubmed/33602341
http://dx.doi.org/10.1186/s40364-021-00268-x

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