Machine learning prediction of prostate cancer from transrectal ultrasound video clips

OBJECTIVE: To build a machine learning (ML) prediction model for prostate cancer (PCa) from transrectal ultrasound video clips of the whole prostate gland, diagnostic performance was compared with magnetic resonance imaging (MRI). METHODS: We systematically collated data from 501 patients—276 with p...

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Detalles Bibliográficos
Autores principales: Wang, Kai, Chen, Peizhe, Feng, Bojian, Tu, Jing, Hu, Zhengbiao, Zhang, Maoliang, Yang, Jie, Zhan, Ying, Yao, Jincao, Xu, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459141/
https://www.ncbi.nlm.nih.gov/pubmed/36091110
http://dx.doi.org/10.3389/fonc.2022.948662

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459141/
https://www.ncbi.nlm.nih.gov/pubmed/36091110
http://dx.doi.org/10.3389/fonc.2022.948662

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