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

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.

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.

Inclusion Criteria:

1. patients aged 18 years or older
2. patients able to give informed consent
3. American Society of Anesthesiology risk class 1,2 or 3

Exclusion Criteria:

1. patients with absolute contraindications to EGD examination
2. patients with a history of previous gastrectomy
3. patients with a serious underlying disease
4. pregnant patients
5. researchers believe that the patient is not suitable to participate in the trial