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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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| Publicado no: | Sci Rep |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2017
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| Assuntos: | |
| Acesso em linha: | 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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