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)...

Descripción completa

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

Internet

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

Ejemplares similares