Artificial intelligence for imaging-based detection of gallbladder cancer: A systematic review and diagnostic test accuracy meta-analysis

doi:10.3748/wjg.123989

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Meta-Analysis

Copyright: ©Author(s) 2027. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Jan 7, 2027; 33(1): 123989
Published online Jan 7, 2027. doi: 10.3748/wjg.123989

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Figure 1 Study selection flow. The diagram follows PRISMA 2020 flow-logic and distinguishes qualitative inclusion from quantitative diagnostic test accuracy eligibility. DTA: Diagnostic test accuracy; GBC: Gallbladder cancer; AI: Artificial intelligence.

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 2027; 33(1): 123989
URL: https://www.wjgnet.com/1007-9327/full/v33/i1/123989.htm
DOI: https://dx.doi.org/10.3748/wjg.123989

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 2027; 33(1): 123989 [DOI: 10.3748/wjg.123989]

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