Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer

Colonoscopy is the most commonly used tool to screen for colorectal cancer (CRC). Here, the authors develop a deep learning model to perform optical diagnosis of CRC by training on a large data set of white-light colonoscopy images and achieve endoscopist-level performance on three independent datas...

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Autores principales: Dejun Zhou, Fei Tian, Xiangdong Tian, Lin Sun, Xianghui Huang, Feng Zhao, Nan Zhou, Zuoyu Chen, Qiang Zhang, Meng Yang, Yichen Yang, Xuexi Guo, Zhibin Li, Jia Liu, Jiefu Wang, Junfeng Wang, Bangmao Wang, Guoliang Zhang, Baocun Sun, Wei Zhang, Dalu Kong, Kexin Chen, Xiangchun Li
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/5c46ece027b64112af1315b6221f8c2b
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Sumario:Colonoscopy is the most commonly used tool to screen for colorectal cancer (CRC). Here, the authors develop a deep learning model to perform optical diagnosis of CRC by training on a large data set of white-light colonoscopy images and achieve endoscopist-level performance on three independent datasets.

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