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

Table 4 Results of full feature machine learning model

Algorithms	Accuracy	F1 score	Sensitivity	Specificity
SVM	0.81	0.793	0.742	0.875
RF	0.714	0.719	0.742	0.688
KNN	0.698	0.678	0.645	0.75
LR	0.789	0.783	0.766	0.813

SVM: Support vector machine; RF: Random forest; KNN: K-nearest neighbors; LR: Logistic regression.

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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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