Io Lei, IanGaya, Daniel R.Robertson, AlexanderSchelde-Olesen, BenedicteMapiye, AliceBhandare, AnirudhLui, Bei BeiShekhar, ChanderValentiner, UrsulaGilabert Roca, PereLaiz Treceño, PabloSeguí Mesquida, SantiParsons, NicholasHuhulea, CristianaWenzek, HagenWhite, ElizabethKoulaouzidis, AnastasiosArasaradnam, Ramesh P.2026-02-162026-02-162025-08-292072-6694https://hdl.handle.net/2445/226894This study assessed the reliability of AI-assisted bowel cleansing scoring in colon capsule endoscopy using the CC-CLEAR scale. While interobserver agreement was excellent with manual scoring among experienced readers, AI-assisted reads did not improve agreement but showed reduced consistency, particularly among less experienced users. The mean AI-assisted scores were significantly lower than manual scores, highlighting potential interpretive challenges. These findings suggest that AI’s effectiveness currently depends on user expertise, reinforcing the importance of further development and refinement required for a robust AI implementation in CCE.15 p.application/pdfengcc-by (c) Ian Io Lei et al., 2025http://creativecommons.org/licenses/by/4.0/Càpsula endoscòpicaAprenentatge automàticIntel·ligència artificialCapsule endoscopyMachine learningArtificial intelligenceinfo:eu-repo/semantics/article7653612026-02-16info:eu-repo/semantics/openAccess