Predicting gastrointestinal bleeding and audio biomarkers based on machine learning analysis of bowel sounds

doi:10.3748/wjg.v32.i14.115162

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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

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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.

World J Gastroenterol. Apr 14, 2026; 32(14): 115162
Published online Apr 14, 2026. doi: 10.3748/wjg.v32.i14.115162

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Figure 7 Receiver operating characteristic curves and area under the curve values of each model. A-E: Show the top 20, 25, 30, 35, and 40 feature subsets; F: Presents the area under the curve for each model under its respective optimal feature subset size. AUC: Area under the curve; SVM: Support vector machine; RF: Random forest; KNN: K-nearest neighbors; LR: Logistic regression.

Citation: Zhang L, Wang MY, Wei SY, Su C, Hu SY, Ren XY, Liu YP, Liu C, Wan Y. Predicting gastrointestinal bleeding and audio biomarkers based on machine learning analysis of bowel sounds. World J Gastroenterol 2026; 32(14): 115162
URL: https://www.wjgnet.com/1007-9327/full/v32/i14/115162.htm
DOI: https://dx.doi.org/10.3748/wjg.v32.i14.115162

Zhang L, Wang MY, Wei SY, Su C, Hu SY, Ren XY, Liu YP, Liu C, Wan Y. Predicting gastrointestinal bleeding and audio biomarkers based on machine learning analysis of bowel sounds. World J Gastroenterol 2026; 32(14): 115162 [DOI: 10.3748/wjg.v32.i14.115162]

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