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Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

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Related Experiment Video

Updated: Jan 13, 2026

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
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Artificial Intelligence Model for Automated Identification of Bowel Preparation for Colonoscopy (AI-PREPOO): A

Kosuke Kojima1,2, Kazuya Takahashi1, Hiroki Maruyama1

  • 1Division of Gastroenterology and Hepatology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.

Journal of Gastroenterology and Hepatology
|January 12, 2026
PubMed
Summary

Artificial intelligence (AI) models were developed to automatically assess bowel preparation for colonoscopy using smartphone images. AI-PREPOO 1 achieved high accuracy, potentially reducing healthcare burdens.

Keywords:
artificial intelligencebowel preparationcolonoscopydeep learning

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Gastroenterology

Background:

  • High-quality colonoscopy relies on adequate bowel preparation.
  • Assessing bowel preparation is often burdensome for patients and providers.
  • Automated assessment tools are needed to streamline this process.

Purpose of the Study:

  • To develop artificial intelligence (AI) models for automated bowel preparation assessment.
  • To identify AI models capable of classifying stool images for colonoscopy readiness.
  • To reduce the burden associated with manual bowel preparation evaluation.

Main Methods:

  • Participants photographed stool images using smartphones post-bowel movement.
  • Images were uploaded and labeled as 'ready' or 'not ready' for colonoscopy.
  • Four deep learning models (AI-PREPOO 1-4) were trained using transfer learning on labeled images.

Main Results:

  • A dataset of 282 stool images was collected and augmented.
  • All developed AI models demonstrated high performance (AUC > 0.90).
  • AI-PREPOO 1 achieved the best diagnostic performance (AUC, 0.95; sensitivity, 0.93; specificity, 0.86).

Conclusions:

  • AI-based models can accurately assess bowel preparation adequacy.
  • AI-PREPOO 1 shows promising, well-balanced diagnostic performance.
  • This AI tool has the potential to simplify bowel preparation assessment and alleviate healthcare burdens.