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Conventional diagnostic approaches, such as colonoscopy and capsule endoscopy, primarily rely on visual inspection and often fail to capture subsurface or biomechanical abnormalities. To address this limitation, an AI\u2010enhanced vibration\u2010assisted capsule is developed for in situ biomechanical sensing of bowel tissues. The self\u2010contained capsule integrates an eccentric vibration motor, triaxial accelerometer, power supply, and wireless communication unit within a swallowable format. During operation, motor\u2010induced oscillations deform surrounding tissue, and the resulting acceleration responses are wirelessly transmitted for real\u2010time analysis. Experiments conducted on ex vivo porcine colon specimens and a soft pneumatic in vitro colon simulator demonstrate that vibration\u2010induced signals capture reproducible mechanical contrasts between normal tissue and lesions of varying relative stiffness. A one\u2010class support vector machine, trained exclusively on normal tissue data, is employed to classify abnormal tissues without requiring extensive annotated datasets. Complementary dynamic modeling further identifies equivalent stiffness parameters, correlating lesion stiffness with abnormal classifications. This work demonstrates a minimally invasive, AI\u2010driven modality for non\u2010visual colorectal cancer detection, establishing the potential of vibration\u2010assisted capsules to provide real\u2010time, patient\u2010friendly screening and to complement existing imaging\u2010based\u00a0diagnostics.<\/jats:p>","DOI":"10.1002\/advs.202517936","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T08:59:58Z","timestamp":1771318798000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AI\u2010Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue"],"prefix":"10.1002","volume":"13","author":[{"given":"Xizheng","family":"Fang","sequence":"first","affiliation":[{"name":"Exeter Small\u2010Scale Robotics Laboratory Engineering Department University of Exeter Exeter 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