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Machine learning classifiers for predicting 3-year progression-free survival and overall survival in patients with gliomas after surgery

Background: To develop machine-learning based models to predict the progression-free survival (PFS) and overall survival (OS) in patients with gliomas and explore the effect of different feature selection methods on the prediction. Methods: We included 505 patients (training cohort, n = 354; validat...

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Detalles Bibliográficos
Autores principales:	Zhang, Bin, Yan, Jing, Chen, Weiqi, Dong, Yuhao, Zhang, Lu, Mo, Xiaokai, Chen, Qiuying, Cheng, Jingliang, Liu, Xianzhi, Wang, Weiwei, Zhang, Zhenyu, Zhang, Shuixing
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Ivyspring International Publisher 2021
Materias:	Research Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890310/ https://www.ncbi.nlm.nih.gov/pubmed/33613747 http://dx.doi.org/10.7150/jca.52183

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