AI-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis
Artificial Intelligence-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis to Achieve Gastric Cancer Risk Assessment
Shandong University
1,500 participants
Jun 1, 2023
OBSERVATIONAL
Conditions
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
Inclusion Criteria1
- Patients aged 18-80 years who undergo the white light endoscope examination Informed consent form provided by the patient.
Exclusion Criteria6
- patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric;
- disorders who cannot participate in gastroscopy;
- Patients with progressive gastric cancer;
- low quality pictures;
- patients with previous surgical procedures on the stomach or esophageal;
- patients who refuse to sign the informed consent form;
Interventions
Endosopists and AI will assess the Kimura-Takemoto classification independently when the patients is eligible.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT05916014