Multimodal data integration for predicting progression risk in castration-resistant prostate cancer using deep learning: a multicenter retrospective study

PurposePatients with advanced prostate cancer (PCa) often develop castration-resistant PCa (CRPC) with poor prognosis. Prognostic information obtained from multiparametric magnetic resonance imaging (mpMRI) and histopathology specimens can be effectively utilized through artificial intelligence (AI)...

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Detalles Bibliográficos

Principais autores:	Chuan Zhou, Yun-Feng Zhang, Sheng Guo, Yu-Qian Huang, Xiao-Ni Qiao, Rong Wang, Lian-Ping Zhao, De-Hui Chang, Li-Ming Zhao, Ming-Xu Da, Feng-Hai Zhou
Formato:	Artigo
Idioma:	Inglês
Publicado:	Frontiers Media S.A. 2024-03-01
Series:	Frontiers in Oncology
Assuntos:	radiomics pathomics castration-resistant prostate cancer deep learning multi-modal
Acceso en liña:	https://www.frontiersin.org/articles/10.3389/fonc.2024.1287995/full
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