Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

ObjectiveTo identify optimal machine-learning methods for the radiomics-based differentiation of gliosarcoma (GSM) from glioblastoma (GBM).Materials and MethodsThis retrospective study analyzed cerebral magnetic resonance imaging (MRI) data of 83 patients with pathologically diagnosed GSM (58 men, 2...

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Bibliographic Details
Main Authors: Zenghui Qian, Lingling Zhang, Jie Hu, Shuguang Chen, Hongyan Chen, Huicong Shen, Fei Zheng, Yuying Zang, Xuzhu Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Oncology
Subjects:
gliosarcoma
glioblastoma
machine learning
radiomics
differentiation
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.699789/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.699789/full

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