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RECRUITING
NCT05916014

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

Sponsor: Shandong University

View on ClinicalTrials.gov

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.

Official title: Artificial Intelligence-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis to Achieve Gastric Cancer Risk Assessment

Key Details

Gender

All

Age Range

18 Years - 80 Years

Study Type

OBSERVATIONAL

Enrollment

1500

Start Date

2023-06-01

Completion Date

2024-12-31

Last Updated

2024-04-12

Healthy Volunteers

No

Interventions

DIAGNOSTIC_TEST

Diagnostic Test: The diagnosis of Artificial Intelligence and endosopists

Endosopists and AI will assess the Kimura-Takemoto classification independently when the patients is eligible.

Locations (1)

Department of Gastrology, QiLu Hospital, Shandong University

Shangdong, Shandong, China