An artificial intelligence model for the pathological diagnosis of invasion depth and histologic grade in bladder cancer

BACKGROUND: Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, we aimed to develop a pathological artificial inte...

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Detalles Bibliográficos
Autores principales: Pan, Jiexin, Hong, Guibin, Zeng, Hong, Liao, Chengxiao, Li, Huarun, Yao, Yuhui, Gan, Qinghua, Wang, Yun, Wu, Shaoxu, Lin, Tianxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9869632/
https://www.ncbi.nlm.nih.gov/pubmed/36691055
http://dx.doi.org/10.1186/s12967-023-03888-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9869632/
https://www.ncbi.nlm.nih.gov/pubmed/36691055
http://dx.doi.org/10.1186/s12967-023-03888-z

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