NCT04384575

Study on the Effectiveness of Gastroscope Operation Quality Control Based on Artificial Intelligence Technology

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,570 (actual)
• Sponsor: Peking University · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Accepted

Summary

This study aims to construct a real-time quality monitoring system based on artificial intelligence technology.

Detailed description

Gastroscopy plays an important role in the detection and diagnosis of upper gastrointestinal diseases. It is necessary for endoscopists to operate gastroscope according to the standardized process, in order to avoid missing early lesions. However, with the rapid increase in the number of endoscopies, the workload of endoscopists increases further. High workload reduces the quality of endoscopy, resulting in incomplete observation of anatomical parts that are easy to be missed in the process of gastroscopy. There are significant differences in the operation level of different endoscopists. Therefore, carrying out artificial intelligence methods has good academic research and practical value for improving the quality of endoscopic diagnosis and treatment. Artificial intelligence devices need to use a large number of endoscopic images, based on this, we intends to collect endoscopic image data from our hospitals for training and validation of the model.

Conditions

• Gastric Cancer

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	blind spots	missed part during map the entire stomach through endoscopy

Timeline

• Start date: 2020-02-22
• Primary completion: 2022-01-13
• Completion: 2022-05-01
• First posted: 2020-05-12
• Last updated: 2023-11-29

Locations

1 site across 1 country: China