Two machine learning methods identify a metastasis-related prognostic model that predicts overall survival in medulloblastoma patients

Approximately 30% of medulloblastoma (MB) patients exhibit metastasis at initial diagnosis, which often leads to a poor prognosis. Here, by using univariate Cox regression analysis, two machine learning methods (Lasso-penalized Cox regression and random survival forest-variable hunting (RSF-VH)), an...

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Detalles Bibliográficos
Autores principales: Chen, Kui, Huang, Bingsong, Yan, Shan, Xu, Siyi, Li, Keqin, Zhang, Kuiming, Wang, Qi, Zhuang, Zhongwei, Wei, Liang, Zhang, Yanfei, Liu, Min, Lian, Hao, Zhong, Chunlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695392/
https://www.ncbi.nlm.nih.gov/pubmed/33159021
http://dx.doi.org/10.18632/aging.103923

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695392/
https://www.ncbi.nlm.nih.gov/pubmed/33159021
http://dx.doi.org/10.18632/aging.103923

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