Predicting the recurrence and overall survival of patients with glioma based on histopathological images using deep learning

BACKGROUND: A deep learning (DL) model based on representative biopsy tissues can predict the recurrence and overall survival of patients with glioma, leading to optimized personalized medicine. This research aimed to develop a DL model based on hematoxylin-eosin (HE) stained pathological images and...

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Detalles Bibliográficos
Autores principales: Luo, Chenhua, Yang, Jiyan, Liu, Zhengzheng, Jing, Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102594/
https://www.ncbi.nlm.nih.gov/pubmed/37064206
http://dx.doi.org/10.3389/fneur.2023.1100933

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102594/
https://www.ncbi.nlm.nih.gov/pubmed/37064206
http://dx.doi.org/10.3389/fneur.2023.1100933

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