Publication Name	World Journal of Gastroenterology
Manuscript ID	123989
DOI	10.3748/wjg.123989
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Meta-Analysis
Article Title	Artificial intelligence for imaging-based detection of gallbladder cancer: A systematic review and diagnostic test accuracy meta-analysis
Manuscript Source	Unsolicited Manuscript
All Author List	Jia-Yun Zhu, Hao Lin, Jing-Wei Zhao and Zi-Yi Yang
Funding Agency and Grant Number	Funding Agency Grant Number Interdisciplinary Program of Shanghai Jiao Tong University No. YG2024QNA19
Corresponding Author	Zi-Yi Yang, MD, Department of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai 200092, China. yangziyi@xinhuamed.com.cn
Key Words	Gallbladder cancer; Artificial intelligence; Deep learning; Radiomics; Diagnostic accuracy; Meta-analysis; Summary receiver operating characteristic
Core Tip	Early diagnosis of gallbladder cancer remains challenging because malignant lesions often mimic benign gallbladder diseases. This study provides the first diagnostic test accuracy meta-analysis focused exclusively on patient-level validation evidence for artificial intelligence-based imaging diagnosis of gallbladder cancer. By separating clinical validation cohorts from image-level development studies, we found that only five datasets were suitable for quantitative synthesis despite 32 eligible publications. Artificial intelligence-assisted imaging achieved high diagnostic performance and may serve as an effective adjunct for lesion triage and radiological decision support, although robust prospective multicenter validation is still required before routine clinical implementation.
Citation	Zhu JY, Lin H, Zhao JW, Yang ZY. Artificial intelligence for imaging-based detection of gallbladder cancer: A systematic review and diagnostic test accuracy meta-analysis. World J Gastroenterol 2026; In press DOI: https://doi.org/10.3748/wjg.123989
PDF	123989-in-press.pdf

Received	2026-06-04 08:25
Peer-Review Started	2026-06-04 08:25
First Decision by Editorial Office Director
Return for Revision	2026-06-18 03:09
Revised	2026-06-29 01:34
Publication Fee Transferred	2026-07-25 14:35
Second Decision by Editor	2026-09-09 02:32
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-09-09 10:08
Articles in Press	2026-09-09 10:08
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1007-9327 (print) and 2219-2840 (online)
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Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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