Publication Name	World Journal of Gastroenterology
Manuscript ID	109389
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Letter to the Editor
Article Title	Insights into a machine learning-based prediction model for colorectal polyp recurrence after endoscopic mucosal resection
Manuscript Source	Unsolicited Manuscript
All Author List	Guang-Yao Li and Lu-Lu Zhai
Funding Agency and Grant Number	Funding Agency Grant Number Wuhu Municipal Science and Technology Bureau Project 2024kj072
Corresponding Author	Lu-Lu Zhai, Chief Physician, MD, Professor, Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No. 17 Lujiang Road, Hefei 230001, Anhui Province, China. jackyzhai123@163.com
Key Words	Colorectal polyp recurrence; Endoscopic mucosal resection; Machine learning; Risk prediction; Clinical implementation; External validation
Core Tip	This letter provides a critical appraisal of a recent machine learning model designed to predict colorectal polyp recurrence after endoscopic mucosal resection. It highlights key methodological issues, such as endpoint selection, imputation transparency, and external validation, while offering constructive recommendations to enhance clinical applicability and alignment with international surveillance guidelines.
Citation	Li GY, Zhai LL. Insights into a machine learning-based prediction model for colorectal polyp recurrence after endoscopic mucosal resection. World J Gastroenterol 2025; In press

Received	2025-05-09 10:21
Peer-Review Started	2025-05-09 10:21
To Make the First Decision
Return for Revision	2025-05-16 22:41
Revised	2025-05-22 14:26
Second Decision	2025-07-25 02:40
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-07-25 06:27
Articles in Press	2025-07-25 06:27
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

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