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March 3, 20260 citationsOpen Access

Inter-and Intraobserver Variability in Bowel Preparation Scoring for Colon Capsule Endoscopy: Impact of AI-Assisted Assessment Feasibility Study

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ILIan Io LeiDGDaniel R. GayaARAlexander Robertson

Key Points

  • AI-assisted scoring did not enhance interobserver agreement among experienced users, revealing limitations in consistency.
  • Manual scoring showed excellent interobserver agreement, while AI-assisted scores were significantly lower, raising interpretive challenges.
  • Analysis using the CC-CLEAR scale indicated that AI's effectiveness is heavily influenced by user expertise and experience.
  • Further development and refinement of AI tools are needed to improve their reliability in clinical practice.

Abstract

This 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.

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Cite This Study

Lei et al. (2025) studied this question.

synapsesocial.com/papers/69a76225c6e9836116a30414https://hdl.handle.net/2445/226894
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