NCT04591145

Multi-center Validation of a Deep Learning Based Bowel Preparation Evaluation System

Validation of a Deep Learning Based Bowel Preparation Evaluation System: A Prospective, Multi-center, Cross-sectional Study

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,400 (estimated)
• Sponsor: Renmin Hospital of Wuhan University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

A deep learning based system to calculate the proportion of Boston Bowel Prep Scale (BBPS) score of 0-1 during withdrawal phase has been constructed previously. This multi-center study is going to perform a prospective observational study to validate the threshold of the adequate proportion.

Detailed description

Inadequate bowel preparation is insufficient for identification of polyps greater than 5 mm. However, bowel preparation assessment involved subjectivity and uncertainty. We constructed a deep learning based system to calculate the proportion of Boston Bowel Prep Scale (BBPS) score of 0-1 during withdrawal phase and performed a prospective observational study to validate the threshold of the adequate proportion.The multi-center study is aimed to verify the extrapolation and robustness of the scoring threshold based on artificial intelligence intestinal cleanliness evaluation system explored in the early stage, and propose a more accurate and quantifiable threshold for evaluating the eligibility of intestinal preparation.

Conditions

• Adenoma
• Bowel Preparation

Interventions

Type	Name	Description
OTHER	Observational group	Patient receive the standard bowel preparation strategy and routine colonoscopy

Timeline

• Start date: 2020-10-09
• Primary completion: 2020-12-31
• Completion: 2020-12-31
• First posted: 2020-10-19
• Last updated: 2020-10-19

Locations

1 site across 1 country: China