| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Clinical and Translational Research |
| Article Title |
Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Sheng-Bing Zhao, Wei Yang, Shu-Ling Wang, Peng Pan, Run-Dong Wang, Xin Chang, Zhong-Qian Sun, Xing-Hui Fu, Hong Shang, Jian-Rong Wu, Li-Zhu Chen, Jia Chang, Pu Song, Ying-Lei Miao, Shui-Xiang He, Lin Miao, Hui-Qing Jiang, Wen Wang, Xia Yang, Yuan-Hang Dong, Han Lin, Yan Chen, Jie Gao, Qian-Qian Meng, Zhen-Dong Jin, Zhao-Shen Li and Yu Bai |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Key R&D Program of China |
2018YFC1313103 |
| National Natural Science Foundation of China |
81670473 |
| "Shu Guang" project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation |
19SG30 |
| Key Area Research and Development Program of Guangdong Province |
2018B010111001 |
| National Natural Science Foundation of China |
81873546 |
|
| Corresponding Author |
Yu Bai, MD, PhD, Assistant Professor, Associate Professor, Department of Gastroenterology, Changhai Hospital, Second Military Medical University/Naval Medical University, No. 168 Changhai Road , Shanghai 200433, China. baiyu1998@hotmail.com |
| Key Words |
Computer-assisted detection; Artificial intelligence; Deep learning; Colonoscopy; Clinical validation; Colorectal polyp |
| Core Tip |
Our study indicated that the deep learning-based computer-assisted detection system trained from the dataset consisting of the largest number of polyps achieved high diagnostic performance on the test dataset of images, colonoscopy videos and clinical validation. This system might aid colonoscopists in finding more polyps and adenomas and deserves to be further validated in multicenter randomized trials. |
| Publish Date |
2021-08-18 08:08 |
| Citation |
Zhao S, Yang W, Wang S, Pan P, Wang R, Chang X, Sun Z, Fu X, Shang H, Wu J, Chen L, Chang J, Song P, Miao YL, He S, Miao L, Jiang HQ, Wang W, Yang X, Dong Y, Lin H, Chen Y, Gao J, Meng QQ, Jin ZD, Li Z, Bai Y. Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning. World J Gastroenterol 2021; 27(31): 5232-5246 |
| URL |
https://www.wjgnet.com/1007-9327/full/v27/i31/5232.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v27.i31.5232 |
