Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images

PURPOSE: We analyzed clinical features and the representative HE-stained pathologic images to predict 5-year overall survival via the deep-learning approach in cervical cancer patients in order to assist oncologists in designing the optimal treatment strategies. METHODS: The research retrospectively...

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Detalles Bibliográficos
Autores principales: Zhang, Kun, Sun, Kui, Zhang, Caiyi, Ren, Kang, Li, Chao, Shen, Lin, Jing, Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356676/
https://www.ncbi.nlm.nih.gov/pubmed/36653539
http://dx.doi.org/10.1007/s00432-022-04446-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356676/
https://www.ncbi.nlm.nih.gov/pubmed/36653539
http://dx.doi.org/10.1007/s00432-022-04446-8

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