NCT05832411

Effect of AI Monitoring Blind Spots of EGD on the Inspection Time and Lesion Dection Rate

Effect of Artificial Intelligence Monitoring Blind Spots of EGD on the Inspection Time and Dection Rate of Neoplastic Lesions

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,672 (estimated)
• Sponsor: Renmin Hospital of Wuhan University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

The goal of this clinic trial is to learn about the effect of AI monitoring blind spots on the inspection time to EGD. Patients are randomly assigned to undergo an EGD with or without the assistance of AI. In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Researchers will compare intervention group to see if it have a shorter inspection time compared with the control group.

Detailed description

The goal of this clinic trial is to evaluate the effect of real-time artificial intelligence for monitoring blind spots on the inspection time of EGD. Patients are randomly assigned to undergo an EGD with or without the assistance of AI. In the AI group, except for the original videos, there is additional information presented to endoscopists:(1)the virtual stomach model monitoring;(2)time;(3)scoring. Researchers will compare intervention group to see if it have a shorter inspection time in the case of non-inferior detection rate of gastric neoplastic lesions.

Conditions

• Upper Gastrointestinal Symptoms

Interventions

Type	Name	Description
DEVICE	Endoangle	there is additional information presented to endoscopists:（1）the virtual stomach model monitoring；（2）time;（3）scoring.

Timeline

• Start date: 2023-07-01
• Primary completion: 2024-05-31
• Completion: 2024-08-31
• First posted: 2023-04-27
• Last updated: 2023-06-22