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

Authors :
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
Source :
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Publication Year :
2020
Publisher :
Nature Portfolio, 2020.

Abstract

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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.5c46ece027b64112af1315b6221f8c2b
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-020-16777-6