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Machine learning applications for prediction of relapse in childhood acute lymphoblastic leukemia

The prediction of relapse in childhood acute lymphoblastic leukemia (ALL) is a critical factor for successful treatment and follow-up planning. Our goal was to construct an ALL relapse prediction model based on machine learning algorithms. Monte Carlo cross-validation nested by 10-fold cross-validat...

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Bibliografski detalji
Izdano u:Sci Rep
Glavni autori: Pan, Liyan, Liu, Guangjian, Lin, Fangqin, Zhong, Shuling, Xia, Huimin, Sun, Xin, Liang, Huiying
Format: Artigo
Jezik:Inglês
Izdano: Nature Publishing Group UK 2017
Teme:
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5547099/
https://ncbi.nlm.nih.gov/pubmed/28784991
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-017-07408-0
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