Survival prediction for patients with glioblastoma multiforme using a Cox proportional hazards denoising autoencoder network

OBJECTIVES: This study aimed to establish and validate a prognostic model based on magnetic resonance imaging and clinical features to predict the survival time of patients with glioblastoma multiforme (GBM). METHODS: In this study, a convolutional denoising autoencoder (DAE) network combined with t...

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Detalles Bibliográficos
Autores principales: Yan, Ting, Yan, Zhenpeng, Liu, Lili, Zhang, Xiaoyu, Chen, Guohui, Xu, Feng, Li, Ying, Zhang, Lijuan, Peng, Meilan, Wang, Lu, Li, Dandan, Zhao, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871481/
https://www.ncbi.nlm.nih.gov/pubmed/36704230
http://dx.doi.org/10.3389/fncom.2022.916511

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871481/
https://www.ncbi.nlm.nih.gov/pubmed/36704230
http://dx.doi.org/10.3389/fncom.2022.916511

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