ArticleDEN open2025
Combination of artificial intelligence endoscopic diagnosis and Kimura-Takemoto classification determined by endoscopic experts may effectively evaluate the stratification of gastric atrophy in post-eradication status.
Article in DEN open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Early Detection of Gastric Cancer: Linking Epidemiology, Pathophysiology, and Innovations in Digestive Endoscopy.Diseases (Basel, Switzerland) · 2026Review
- World Endoscopy Organization Position Statements for Artificial Intelligence in Endoscopic Diagnosis of Gastric Epithelial Neoplasia.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Review
- Integrated endoscopy: a new method for improving the diagnostic accuracy ofGastroenterology report · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Since it is difficult for expert endoscopists to diagnose early gastric cancer in post-eradication status, it may be critical to evaluate the stratification of high-risk groups using the advance of gastric atrophy or intestinal metaplasia. We tried to determine whether the combination of endoscopic artificial intelligence (AI) diagnosis for the evaluation of gastric atrophy could be a useful tool in both pre- and post-eradication status. Methods: 270 Results: There were significant associations between the severity of gastric atrophy determined by AI endoscopic diagnosis and not having a regular arrangement of collecting venules in angle, visibility of vascular pattern, and mucus using Kyoto classification in Conclusion: A combination of gastric atrophy determined by AI endoscopic diagnosis and Kimura-Takemoto classification may be a useful tool for the prediction of high-risk groups in post-eradication status.
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Registered trials
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