A multicenter study of artificial intelligence-aided software for detecting visible clinically significant prostate cancer on mpMRI

BACKGROUND: AI-based software may improve the performance of radiologists when detecting clinically significant prostate cancer (csPCa). This study aims to compare the performance of radiologists in detecting MRI-visible csPCa on MRI with and without AI-based software. MATERIALS AND METHODS: In tota...

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Detalles Bibliográficos
Autores principales: Sun, Zhaonan, Wang, Kexin, Kong, Zixuan, Xing, Zhangli, Chen, Yuntian, Luo, Ning, Yu, Yang, Song, Bin, Wu, Pengsheng, Wang, Xiangpeng, Zhang, Xiaodong, Wang, Xiaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149551/
https://www.ncbi.nlm.nih.gov/pubmed/37121983
http://dx.doi.org/10.1186/s13244-023-01421-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149551/
https://www.ncbi.nlm.nih.gov/pubmed/37121983
http://dx.doi.org/10.1186/s13244-023-01421-w

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