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The Efficacy of AI-Driven Feces Identification for Bowel Preparation Prior to Colonoscopy

NCT07453056 · Status: ENROLLING_BY_INVITATION · Phase: NA · Type: INTERVENTIONAL · Enrollment: 340

Last updated 2026-03-05

No results posted yet for this study

Summary

The objective is to enhance diagnostic outcomes by ensuring thorough bowel cleanliness through AI-driven stool identifying system for bowel preparation in subjects undergoing colonoscopy.Colonoscopy is a key procedure for the prevention and early detection of colorectal cancer, with its diagnostic accuracy highly dependent on the quality of bowel preparation. Inadequate bowel cleansing can lead to missed lesions, prolonged procedure times, and the need for repeat examinations. Despite public health efforts that have improved screening rates over the past decade, the adequacy of bowel preparation has remained relatively unchanged, posing a persistent clinical challenge.

With the rapid advancement of artificial intelligence (AI) technologies, deep learning-based image recognition has demonstrated outstanding performance in medical imaging applications. Recent studies have shown that AI can assist in real-time evaluation of stool appearance, providing patients with immediate feedback and personalized instructions to improve bowel preparation quality. Integrating AI systems into bowel cleansing protocols has the potential to enhance patient compliance, optimize bowel cleanliness, and consequently improve the diagnostic yield of colonoscopy.

This study aims to evaluate the efficacy of an AI-based stool identifying system (AI-SIS), combined with the use of a Prepackaged Low Residue Diet (PLD) and standard bowel preparation instructions. Through a prospective, randomized, evaluator-blind, parallel-group clinical trial design, the study seeks to generate scientific evidence supporting the integration of AI technology into routine bowel preparation practices.

Conditions

  • AI App Improves Bowel Preparation Quality for Colonoscopy

Interventions

OTHER

A Prospective, Randomized, Evaluator Blind, Parallel Study of the Efficacy of AI-driven feces identifying for the Bowel Preparation Prior to Colonoscopy

educational leaflet and APP for reaching AI-SIS for AI aid

OTHER

educational leaflet without APP

educational leaflet without APP

Sponsors & Collaborators

  • Fu Jen Catholic University Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
20 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-09-04
Primary Completion
2026-06-30
Completion
2026-06-30

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07453056 on ClinicalTrials.gov