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Clinical Trial Summary

In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control. This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control. This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms


NCT number NCT06406062
Study type Observational
Source Renmin Hospital of Wuhan University
Contact Honggang Yu, Doctor
Phone 18771146096
Email wjlnsm@163.com
Status Not yet recruiting
Phase
Start date May 20, 2024
Completion date December 30, 2025

See also
  Status Clinical Trial Phase
Recruiting NCT03279783 - LCI (Linked Color Imaging) for Adenoma Detection in the Right Colon N/A
Completed NCT03775811 - In Vivo Computer-aided Prediction of Polyp Histology on White Light Colonoscopy