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Articles Published Processes
4/15/2026 6:47:27 AM | Browse: 0 | Download: 0
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Received |
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2025-11-18 10:52 |
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Peer-Review Started |
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2025-11-19 03:25 |
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First Decision by Editorial Office Director |
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2025-12-09 09:59 |
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Return for Revision |
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2025-12-09 09:59 |
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Revised |
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2025-12-20 10:06 |
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Publication Fee Transferred |
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2025-12-24 06:22 |
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Second Decision by Editor |
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2026-01-28 02:43 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-28 08:09 |
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Articles in Press |
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2026-01-28 08:09 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-04-01 00:35 |
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Publish the Manuscript Online |
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2026-04-15 06:47 |
| 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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2026. 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 |
Deep learning-based multimodal model for predicting on-treatment histological outcomes in chronic hepatitis B-associated advanced liver fibrosis
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Wei Han, Ding-Yuan Cheng, Quan-Wei He, Si-Hao Wang, Shu-Juan Gong, Yan Chen and Yong-Ping Yang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| State Key Projects Specialized on Infectious Disease, Chinese Ministry of Science and Technology |
2013ZX10005002 |
| Beijing Key Research Project of Special Clinical Application |
Z221100007422002 |
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| Corresponding Author |
Yong-Ping Yang, Liver Disease Research Center, Hainan Hospital of Chinese PLA General Hospital, Haitang Bay, Sanya 572013, Hainan Province, China. yongpingyang@hotmail.com |
| Key Words |
Chronic hepatitis B-related liver fibrosis; On-treatment outcome; Deep learning; Whole-slide images; Multimodal predictive model |
| Core Tip |
This study presents a multimodal model that integrates pathological slide staining with clinical features to predict the probability of histological reversal following standard antiviral therapy in patients with advanced chronic hepatitis B-related fibrosis. The model demonstrates robust predictive accuracy in both internal validation and external test sets. This methodology supports patient risk stratification and informs the development of personalized, optimized treatment strategies. |
| Publish Date |
2026-04-15 06:47 |
| Citation |
Han W, Cheng DY, He QW, Wang SH, Gong SJ, Chen Y, Yang YP. Deep learning-based multimodal model for predicting on-treatment histological outcomes in chronic hepatitis B-associated advanced liver fibrosis. World J Gastroenterol 2026; 32(15): 116679 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i15/116679.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i15.116679 |
© 1993-2026 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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