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Related Experiment Video

Updated: Jan 14, 2026

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists
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Artificial Intelligence in Colonoscopy: A Tool, Not a Necessity for Experts.

Raveena Karthikeyan1, Kristin Delfino2, Bridget Mcclain3

  • 1Surgery, Southern Illinois University (SIU) School of Medicine, Springfield, USA.

Cureus
|October 27, 2025
PubMed
Summary

Artificial intelligence (AI) for colonoscopy did not significantly improve polyp or adenoma detection rates for an experienced endoscopist. However, AI-assisted colonoscopy was linked to a shorter procedure time.

Keywords:
adenoma detection rateartificial intelligencecolon polypcolonoscopyexperienced endoscopist

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Area of Science:

  • Gastroenterology
  • Medical technology
  • Artificial intelligence in medicine

Background:

  • AI tools show promise for improving polyp detection during colonoscopy.
  • Real-world AI performance varies, especially with experienced endoscopists.
  • This study assesses AI's impact on adenoma detection rate (ADR) and polyp detection rate (PDR) for a single, high-volume endoscopist.

Purpose of the Study:

  • To evaluate the effectiveness of AI-assisted colonoscopy (AIAC) in enhancing ADR and PDR.
  • To determine if AI impacts colonoscopy quality metrics when used by an experienced endoscopist.
  • To analyze the effect of AI on procedure time and detection rates in a real-world clinical setting.

Main Methods:

  • Retrospective analysis of colonoscopies from July 2019 to June 2023.
  • Inclusion of screening or surveillance colonoscopies performed by one experienced endoscopist.
  • Comparison of outcomes between pre-AI-assisted colonoscopy (pre-AIAC) and AI-assisted colonoscopy (AIAC) groups.

Main Results:

  • No statistically significant difference in ADR (35% vs. 31%) or PDR (42% vs. 38%) between pre-AIAC and AIAC groups.
  • Adenomas per colonoscopy also showed no significant change (0.62 vs. 0.51).
  • AI-assisted colonoscopy was associated with a significantly shorter mean withdrawal time (9.34 vs. 10.44 minutes).

Conclusions:

  • AI-assisted colonoscopy may not substantially improve ADR or PDR for experienced endoscopists.
  • AIAC use correlated with a significant reduction in colonoscopy withdrawal time.
  • Further investigation is warranted to understand AI's role in diverse clinical scenarios.