Publication Name	World Journal of Gastroenterology
Manuscript ID	125206
DOI	10.3748/wjg.125206
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Observational Study
Article Title	Deep learning for predicting high-grade dysplasia in colorectal polyps using white-light endoscopy
Manuscript Source	Unsolicited Manuscript
All Author List	Yue Zhang, Shuang Yan, Ying-Jie Li, Qian-Xun Li and Li-Juan Wei
Funding Agency and Grant Number
Corresponding Author	Li-Juan Wei, Director, Full Professor, Department of Gastroenterology and Digestive Endoscopy Center, The Second Hospital of Jilin University, No. 218 Ziqiang Street, Nanguan District, Changchun 130000, Jilin Province, China. 1835529876@qq.com
Key Words	Artificial intelligence; Colorectal polyps; High-grade dysplasia; White-Light imaging; Deep learning; Endoscopy
Core Tip	We developed and externally validated a deep learning model based on routine white-light endoscopy for predicting high-grade dysplasia in colorectal polyps. The model maintained stable performance across two independent external cohorts and achieved diagnostic accuracy comparable to experienced endoscopists. Because it relies only on routinely acquired white-light images, the proposed approach may facilitate broad clinical implementation as a decision-support tool for colorectal polyp risk stratification.
Citation	Zhang Y, Yan S, Li YJ, Li QX, Wei LJ. Deep learning for predicting high-grade dysplasia in colorectal polyps using white-light endoscopy. World J Gastroenterol 2026; In press DOI: https://doi.org/10.3748/wjg.125206
PDF	125206-in-press.pdf

Received	2026-07-03 08:21
Peer-Review Started	2026-07-03 08:22
First Decision by Editorial Office Director
Return for Revision	2026-07-23 06:52
Revised	2026-07-31 17:47
Publication Fee Transferred	2026-08-25 04:29
Second Decision by Editor	2026-09-20 02:51
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-09-20 10:48
Articles in Press	2026-09-20 10:48
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1007-9327 (print) and 2219-2840 (online)
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