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Clinical Trial 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.


Clinical Trial 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. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05916014
Study type Observational
Source Shandong University
Contact yanqing Li, MD, PHD
Phone 0531182169385
Email liyanqing@sdu.edu.cn
Status Recruiting
Phase
Start date June 1, 2023
Completion date December 31, 2024

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