NCT06406062

Artificial Intelligence-assisted System in Colonoscopy

To Evaluate the Effectiveness and Safety of an Artificial Intelligence-assisted System in Colonoscopy in a Real-world Obsevational Multicenter Study

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 7,500 (estimated)
• Sponsor: Renmin Hospital of Wuhan University · Academic / Other
• Sex: All
• Age: 50 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Adenoma Colon Polyp

Interventions

Type	Name	Description
DEVICE	ANDOANGEL	Polyps were identified by endoscopists assisted by an AI system: rectangular box marks; Monitoring of ileocecal position: whether blindness was reached was displayed in the lower left corner of the interface. Mirror entry and exit time monitoring: the operation time is displayed in the upper left corner of the interface. Colonoscopy withdrawal speed monitoring: the relative withdrawal speed was displayed on the left side of the interface.

Timeline

• Start date: 2024-05-20
• Primary completion: 2025-12-30
• Completion: 2025-12-30
• First posted: 2024-05-09
• Last updated: 2025-04-13

Locations

1 site across 1 country: China