Artificial intelligence and machine learning applications in abdominal tuberculosis diagnosis: A scoping review and translational roadmap

doi:10.35712/aig.123751

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Artificial Intelligence in Gastroenterology

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2644-3236

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

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Copyright: ©Author(s) 2026. 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.

Artif Intell Gastroenterol. Aug 8, 2026; 7(2): 123751
Published online Aug 8, 2026. doi: 10.35712/aig.123751

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Figure 4 Temporal publication trends (2020-2025) and modality distribution. Updated with n = 16 original articles (+ 1 systematic review = 17 total). Sixteen original retrospective studies (total n = 16). Excludes the systematic review by Sachan et al[16]. CT: Computed tomography; MRE: Magnetic resonance elastography; CNN: Convolutional neural network; NLP: Natural language processing.

Citation: Kaushik K, Pathania J, Singh PK, Dinkar M, Pathania V. Artificial intelligence and machine learning applications in abdominal tuberculosis diagnosis: A scoping review and translational roadmap. Artif Intell Gastroenterol 2026; 7(2): 123751
URL: https://www.wjgnet.com/2644-3236/full/v7/i2/123751.htm
DOI: https://dx.doi.org/10.35712/aig.123751

Kaushik K, Pathania J, Singh PK, Dinkar M, Pathania V. Artificial intelligence and machine learning applications in abdominal tuberculosis diagnosis: A scoping review and translational roadmap. Artif Intell Gastroenterol 2026; 7(2): 123751 [DOI: 10.35712/aig.123751]

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