{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T20:13:37Z","timestamp":1790626417731,"version":"4.1.0"},"reference-count":23,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["DEN Open"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Since it is difficult for expert endoscopists to diagnose early gastric cancer in post\u2010eradication status, it may be critical to evaluate the stratification of high\u2010risk 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\u2010 and post\u2010eradication status.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>270 <jats:italic>Helicobacter pylori<\/jats:italic>\u2010positive outpatients (Study I) were enrolled and Study II was planned to compare patients (<jats:italic>n<\/jats:italic>\u00a0=\u00a072) with pre\u2010eradication therapy with post\u2010eradication therapy. Assessment of endoscopic appearance was evaluated by the Kyoto classification and Kimura\u2010Takemoto classification. The trained neural network generated a continuous number between 0 and 1 for gastric atrophy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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 <jats:italic>H. pylori<\/jats:italic>\u2010positive gastritis. There were significant differences (<jats:italic>p<\/jats:italic>\u00a0=\u00a00.037 and <jats:italic>p<\/jats:italic>\u00a0=\u00a00.014) in the severity of gastric atrophy between the high\u2010risk group and low\u2010risk group based on the combination of Kimura\u2010Takemoto classification and endoscopic AI diagnosis in pre\u2010 and post\u2010eradication status. The area under the curve values of the severity of gastric atrophy (0.674) determined by the combination of Kimura\u2010Takemoto classification and gastric atrophy determined by AI diagnosis was higher than that determined by Kimura\u2010Takemoto classification alone in post\u2010eradication status.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>A combination of gastric atrophy determined by AI endoscopic diagnosis and Kimura\u2010Takemoto classification may be a useful tool for the prediction of high\u2010risk groups in post\u2010eradication status.<\/jats:p><\/jats:sec>","DOI":"10.1002\/deo2.70029","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T08:22:56Z","timestamp":1731399776000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Combination of artificial intelligence endoscopic diagnosis and Kimura\u2010Takemoto classification determined by endoscopic experts may effectively evaluate the stratification of gastric atrophy in post\u2010eradication status"],"prefix":"10.1002","volume":"5","author":[{"given":"Kumiko","family":"Kirita","sequence":"first","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0502-8646","authenticated-orcid":false,"given":"Seiji","family":"Futagami","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ken","family":"Nakamura","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuhei","family":"Agawa","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nobue","family":"Ueki","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4386-6288","authenticated-orcid":false,"given":"Kazutoshi","family":"Higuchi","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mayu","family":"Habiro","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rie","family":"Kawawa","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Nippon Medical School Hospital Graduate School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusuke","family":"Kato","sequence":"additional","affiliation":[{"name":"AI Medical Service, Inc.  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