Overview
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.
Description
Grading endoscopic atrophy according to the Kimura-Takemoto classification can assess the risk of gastric neoplasia development. The higher the score, the more severe the degree of atrophic gastritis. 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 of atrophic gastritis to achieve gastric cancer risk assessment.
Eligibility
Inclusion Criteria:
Patients aged 18-80 years who undergo the white light endoscope examination Informed
consent form provided by the patient.
Exclusion Criteria:
1. patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric;
2. disorders who cannot participate in gastroscopy;
3. Patients with progressive gastric cancer;
4. low quality pictures;
5. patients with previous surgical procedures on the stomach or esophageal;
6. patients who refuse to sign the informed consent form;