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Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma

Purpose: The aim of this study was to test whether radiomics-based machine learning can enable the better differentiation between glioblastoma (GBM) and anaplastic oligodendroglioma (AO). Methods: This retrospective study involved 126 patients histologically diagnosed as GBM (n = 76) or AO (n = 50)...

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Detalles Bibliográficos
Autores principales:	Fan, Yimeng, Chen, Chaoyue, Zhao, Fumin, Tian, Zerong, Wang, Jian, Ma, Xuelei, Xu, Jianguo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2019
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848260/ https://www.ncbi.nlm.nih.gov/pubmed/31750250 http://dx.doi.org/10.3389/fonc.2019.01164

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