UnknownNot Applicable

AI-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis

China1,500 participantsStarted 2023-06-01

Plain-language 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.

Who can participate

Age range18 Years – 80 Years

SexALL

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Exclusion criteria

✕. 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;

What they're measuring

Accuracy of AI model to diagnose the Kimura-Takemoto classification

Timeframe: 2 years

Sensitivity of AI model to diagnose the Kimura-Takemoto classification

Timeframe: 2 years

Specificity of AI model to diagnose the Kimura-Takemoto classification

Timeframe: 2 years

Trial details

NCT IDNCT05916014

SponsorShandong University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2024-12-31

Contact for this trial

yanqing Li, MD, PHD

0531182169385 liyanqing@sdu.edu.cn

View on ClinicalTrials.gov More Atrophic Gastritis trials