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Development and Validation of an Artificial Intelligence-assisted System for Bowel Cleanliness Assessment Based on Withdrawal Distance Weighting

NCT07150130 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 700

Last updated 2025-09-02

No results posted yet for this study

Summary

To address the limitations of current AI-based systems that rely on the assumption of a "constant withdrawal speed," this study proposes the integration of the UPD-3 endoscopic positioning system. By using colonoscope withdrawal videos in combination with UPD-3 imaging data as training samples, we aim to develop an AI-powered bowel cleanliness assessment system that incorporates "withdrawal distance" as a weighting factor. This approach is expected to yield a more reliable, objective, and clinically applicable intelligent assessment system that better aligns with real-world clinical practice and endoscopists' operational habits.

Conditions

  • Colorectal Adenoma

Interventions

OTHER

No Intervention: Observational Cohort

No Intervention: Observational Cohort

Sponsors & Collaborators

  • Fudan University

    lead OTHER

Principal Investigators

  • Danian Ji, M.D. · Huadong Hospital

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-10-01
Primary Completion
2028-10-01
Completion
2028-10-01

Countries

  • China

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 NCT07150130 on ClinicalTrials.gov