Publication Name	World Journal of Gastroenterology
Manuscript ID	116679
Country	China

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
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
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
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.
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; In press

Received	2025-11-18 10:52
Peer-Review Started	2025-11-19 03:25
First Decision by Editorial Office Director	2025-12-09 09:59
Return for Revision	2025-12-09 09:59
Revised	2025-12-20 10:06
Publication Fee Transferred	2025-12-24 06:22
Second Decision by Editor	2026-01-28 02:43
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-01-28 08:09
Articles in Press	2026-01-28 08:09
Edit the Manuscript by Language Editor
Typeset the Manuscript

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