Cargando…
AI-predicted mpMRI image features for the prediction of clinically significant prostate cancer
PURPOSE: To evaluate the feasibility of using mpMRI image features predicted by AI algorithms in the prediction of clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: This study analyzed patients who underwent prostate mpMRI and radical prostatectomy (RP) at the Affiliated Hospita...
Autores principales: | Li, Song, Wang, Ke-Xin, Li, Jia-Lei, He, Yi, Wang, Xiao-Ying, Tang, Wen-Rui, Xie, Wen-Hua, Zhu, Wei, Wu, Peng-Sheng, Wang, Xiang-Peng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560153/ https://www.ncbi.nlm.nih.gov/pubmed/37553543 http://dx.doi.org/10.1007/s11255-023-03722-x |
Ejemplares similares
-
Role of mpMRI of the prostate in screening for prostate cancer
por: Wallis, Christopher J. D., et al.
Publicado: (2017) -
Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI
por: Ma, Zengni, et al.
Publicado: (2023) -
The combined value of mpUS and mpMRI-TRUS fusion for the diagnosis of clinically significant prostate cancer
por: Zhang, Xin, et al.
Publicado: (2022) -
Differential diagnosis of uncommon prostate diseases: combining mpMRI and clinical information
por: Han, Chao, et al.
Publicado: (2021) -
Mischievous malakoplakia: A potential pitfall of mpMRI of the prostate?
por: Rezaee, Michael E., et al.
Publicado: (2020)