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Articles Published Processes
1/22/2026 8:14:07 AM | Browse: 62 | Download: 266
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Received |
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2025-08-27 23:13 |
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Peer-Review Started |
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2025-08-27 23:13 |
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First Decision by Editorial Office Director |
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2025-11-04 09:38 |
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Return for Revision |
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2025-11-04 09:38 |
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Revised |
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2025-11-22 15:46 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2025-12-17 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-12-17 13:53 |
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Articles in Press |
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2025-12-17 13:53 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-01-15 01:14 |
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Publish the Manuscript Online |
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2026-01-22 08:14 |
| 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
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| 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 Study |
| Article Title |
Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Yan-Qiu Li, Zhuo-Jun Li, Yong-Qi Li, Ying Feng and Xian-Bo Wang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the High-level Chinese Medicine Key Discipline Construction Project |
zyyzdxk-2023005 |
| Capital’s Funds for Health Improvement and Research |
2024-1-2173 |
| National Natural Science Foundation of China |
82474419 |
| National Natural Science Foundation of China |
82474426 |
| Beijing Municipal Natural Science Foundation |
7232272 |
| Beijing Traditional Chinese Medicine Technology Development Fund Project |
BJZYZD-2023-12 |
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| Corresponding Author |
Xian-Bo Wang, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Chaoyang District, Beijing 100015, China. wangxb@ccmu.edu.cn |
| Key Words |
Hepatitis B; Liver cirrhosis; Clinically significant portal hypertension; Machine learning; Liver-related events; Prediction model |
| Core Tip |
This study developed and validated machine learning models to predict liver-related events in patients with compensated hepatitis B virus-related cirrhosis and clinically significant portal hypertension. Among five models, extreme gradient boosting and random forest achieved the best accuracy and clinical utility. The liver stiffness measurement-to-platelet ratio (LPR) emerged as the most influential predictor, interacting with hemoglobin, international normalized ratio, and spleen thickness. These findings highlight machine learning based on LPR as a robust noninvasive method and provide a novel, interpretable tool for early risk stratification and personalized management in compensated cirrhosis. |
| Publish Date |
2026-01-22 08:14 |
| Citation |
Li YQ, Li ZJ, Li YQ, Feng Y, Wang XB. Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension. World J Gastroenterol 2026; 32(4): 113492 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i4/113492.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i4.113492 |
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