The role of deep learning‐based survival model in improving survival prediction of patients with glioblastoma

This retrospective study has been conducted to validate the performance of deep learning‐based survival models in glioblastoma (GBM) patients alongside the Cox proportional hazards model (CoxPH) and the random survival forest (RSF). Furthermore, the effect of hyperparameters optimization methods on...

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Detalles Bibliográficos
Autores principales: Moradmand, Hajar, Aghamiri, Seyed Mahmoud Reza, Ghaderi, Reza, Emami, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Clinical Cancer Researcher
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525162/
https://www.ncbi.nlm.nih.gov/pubmed/34453413
http://dx.doi.org/10.1002/cam4.4230

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525162/
https://www.ncbi.nlm.nih.gov/pubmed/34453413
http://dx.doi.org/10.1002/cam4.4230

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