BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
1/16/2026 11:31:18 AM | Browse: 1 | Download: 0
 |
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 |
|
2026-01-09 03:28 |
|
Publish the Manuscript Online |
|
2026-01-16 11:31 |
| 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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2025. 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 |
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 |
| ORCID |
|
| 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. |
| Publish Date |
2026-01-16 11:31 |
| Citation |
Lu C, Cheng HY, Zhu RK, Zhou YD, Sun KF, Xu L, Sang JZ, Chen JE, 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 2026; 32(3): 115527 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i3/115527.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i3.115527 |
© 2004-2026 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
