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A new AI tool, Colon-Pilot, accurately applies colonoscopy surveillance guidelines and quality benchmarks, outperforming human endoscopists. This system enhances colorectal cancer prevention by improving efficiency and quality.

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Area of Science:

  • Gastroenterology
  • Artificial Intelligence in Medicine
  • Health Informatics

Background:

  • Accurate colonoscopy surveillance requires adherence to guidelines (2020 USMSTF) and quality benchmarks (2024 ACG/ASGE), which are challenging in practice.
  • Colon-Pilot, a large language model (LLM)-powered clinical decision support system (CDSS) using GPT-4o, was developed to automate and standardize these functions.

Purpose of the Study:

  • To develop and validate Colon-Pilot for automating colonoscopy surveillance recommendations and quality benchmarking.
  • To assess the system's accuracy in applying USMSTF guidelines and meeting ACG/ASGE quality indicators.

Main Methods:

  • Human-in-the-loop validation: Colon-Pilot's surveillance recommendations for 596 colonoscopies were compared against expert consensus and 2020 USMSTF guidelines.
  • Automated administrative audit: Colon-Pilot was applied to 42,632 colonoscopies to calculate 2024 ACG/ASGE quality indicators, with auto-generated recommendations subject to safety criteria for manual review.

Main Results:

  • Colon-Pilot achieved 97.5% guideline-concordant accuracy in automated cases, significantly outperforming original endoscopist recommendations (69.7%).
  • The system exceeded 2024 quality targets, including Adenoma Detection Rate (49.8%), Sessile Serrated Lesion Detection Rate (17.7%), bowel preparation adequacy (91.8%), and cecal intubation rate (97.4%).
  • Colon-Pilot recommended appropriate surveillance intervals with high accuracy, flagging only 12.4% of cases for manual review.

Conclusions:

  • Colon-Pilot demonstrates high fidelity in applying surveillance guidelines and automated quality benchmarking for colonoscopies.
  • The LLM-powered system outperforms unassisted endoscopists in guideline adherence, offering a scalable solution for improving colorectal cancer prevention.
  • Combining safety protocols with automated reporting, Colon-Pilot enhances both efficiency and quality in clinical practice.