Publication Name	World Journal of Gastroenterology
Manuscript ID	115527
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Retrospective Cohort Study
Article Title	Application of machine learning models in predicting the risk of thromboembolic events in patients with nonvariceal gastrointestinal bleeding
Manuscript Source	Unsolicited Manuscript
All Author List	Chao Lu, Hao-Yang Cheng, Ren-Ke Zhu, Yi-De Zhou, Ke-Fang Sun, Lei Xu, Jian-Zhong Sang, Jiao-E Chen, Chao-Hui Yu, Yu-Lu Qin and Lan Li
Funding Agency and Grant Number
Corresponding Author	Lan Li, Chief Physician, Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University, No. 79 Qingchun Road, Hangzhou 310003, Zhejiang Province, China. nalil@zju.edu.cn
Key Words	Nonvariceal gastrointestinal bleeding; Thromboembolic event; Machine learning; Categorical boosting; D-dimer
Core Tip	This multicenter study developed and validated five machine learning models to predict thromboembolic risk in patients with nonvariceal gastrointestinal bleeding. Using ten key clinical variables identified by categorical boosting and SHapley Additive exPlanations analysis, all models showed superior predictive performance to D-dimer alone, with the categorical boosting model achieving the best calibration and accuracy. These models can help clinicians identify high-risk patients for early intervention while reducing unnecessary monitoring in low-risk individuals.
Citation	Lu C, Cheng HY, Zhu RK, Zhou YD, Sun KF, Xu L, Sang JZ, Chen EJ, Yu CH, Qin YL, Li L. Application of machine learning models in predicting the risk of thromboembolic events in patients with nonvariceal gastrointestinal bleeding. World J Gastroenterol 2025; In press

Received	2025-10-21 02:13
Peer-Review Started	2025-10-21 02:13
First Decision by Editorial Office Director	2025-10-30 09:36
Return for Revision	2025-10-30 09:36
Revised	2025-11-10 03:04
Publication Fee Transferred	2025-11-11 14:40
Second Decision by Editor	2025-12-16 02:39
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2025-12-16 08:04
Articles in Press	2025-12-16 08:04
Edit the Manuscript by Language Editor
Typeset the Manuscript

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