Artificial Intelligence-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis to Achieve Gastric Cancer Risk Assessment
Status: Recruiting
Location: See location...
Intervention Type: Diagnostic test
Study Type: Observational
SUMMARY
Grading endoscopic atrophy according to the Kimura-Takemoto classification can assess the risk of gastric neoplasia development. However, the false negative rate of chronic atrophic gastritis is high due to the varying diagnostic standardization and diagnostic experience and levels of endoscopists. Therefore, this study aims to develop an AI model to identify the Kimura-Takemoto classification.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 80
Healthy Volunteers: f
View:
• Patients aged 18-80 years who undergo the white light endoscope examination Informed consent form provided by the patient.
Locations
Other Locations
China
Department of Gastrology, QiLu Hospital, Shandong University
RECRUITING
Shangdong
Contact Information
Primary
yanqing Li, MD, PHD
liyanqing@sdu.edu.cn
0531182169385
Time Frame
Start Date: 2023-06-01
Estimated Completion Date: 2024-12-31
Participants
Target number of participants: 1500
Treatments
Chronic atrophic gastritis observed by white light endoscope
Get pictures from gastric antrum,gastric angle,lesser curvature of gastric body, cardia, gastric fundus, greater curvature of gastric body by white light endoscope
Related Therapeutic Areas
Sponsors
Collaborators: Linyi County People's Hospital,Dezhou,China
Leads: Shandong University