NCT05829590

AI-assisted Colonoscopy Report System In Improving Reporting Quality

Speech and Image Recognition Based System in Improving Reporting Quality During Colonoscopy

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 10 (estimated)
• Sponsor: Renmin Hospital of Wuhan University · Academic / Other
• Sex: All
• Age: 18 Years – 70 Years
• Healthy volunteers: Accepted

Summary

In this study, the investigators proposed a prospective study about the effectiveness of speech and image recognition-based system in improving reporting quality during colonoscopy for colonoscopy report quality in endoscopists. The participants would be divided into two groups. For the collected colonoscopy videos, group A would record their observations with the assistance of the artificial intelligence system. The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions. Group B would complete the endoscopy report without special prompts. After a period of washout period, the two groups switched, that is, group A without AI assistance and group B with AI assistance to complete the colonoscopy report. Then, the completeness of the colonoscopy report, the completeness of capturing anatomical landmarks and detected lesions, the completeness of structured description, the accuracy of lesion reporting, the time for reporting and the satisfaction with the reporting system are compared with or without AI assistance.

Conditions

• Artificial Intelligence
• Colonoscopy

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Artificial intelligence assistant system	The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions based on speech recognition and deep learning.

Timeline

• Start date: 2023-05-15
• Primary completion: 2023-06-15
• Completion: 2023-07-31
• First posted: 2023-04-25
• Last updated: 2023-04-25

Locations

1 site across 1 country: China