An automated approach for predicting glioma grade and survival of LGG patients using CNN and radiomics

OBJECTIVES: To develop and validate an efficient and automatically computational approach for stratifying glioma grades and predicting survival of lower-grade glioma (LGG) patients using an integration of state-of-the-art convolutional neural network (CNN) and radiomics. METHOD: This retrospective s...

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Detalles Bibliográficos
Autores principales: Xu, Chenan, Peng, Yuanyuan, Zhu, Weifang, Chen, Zhongyue, Li, Jianrui, Tan, Wenhao, Zhang, Zhiqiang, Chen, Xinjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413530/
https://www.ncbi.nlm.nih.gov/pubmed/36033433
http://dx.doi.org/10.3389/fonc.2022.969907

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413530/
https://www.ncbi.nlm.nih.gov/pubmed/36033433
http://dx.doi.org/10.3389/fonc.2022.969907

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