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

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorFudan University

About this trial

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.

Eligibility criteria

Qualifiers

Clear colonoscopy images suitable for BBPS scoring

Complete and clear colonoscopy videos suitable for BBPS scoring

Clear colonoscopy videos with a stable UPD-3 positioning system, without signal drift, disappearance, or other disruptions

Disqualifiers

Blurred colonoscopy images

Colonoscopy images taken from the small intestine or outside the patient's body

Colonoscopy images captured during irrigation or instrument manipulation

Colonoscopy images obtained during chromoendoscopy

Trial design

Treatments tested in this trial

  • No Intervention: Observational Cohort

Treatment groups

700 Participants
are divided into 4 treatment groups

Sponsors and collaborators