{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:55:21Z","timestamp":1760061321291,"version":"build-2065373602"},"reference-count":20,"publisher":"Georg Thieme Verlag KG","issue":"CP","license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"AI Medical Service Inc."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Endosc Int Open"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Artificial intelligence (AI) is expected to enhance the ability of endoscopists to detect gastric neoplastic lesions; however, its effectiveness among highly skilled Japanese expert endoscopists has not been validated. We developed a novel AI-assisted diagnostic tool for detection of gastric neoplastic lesions and evaluated its utility by comparing the diagnostic performance of endoscopists with and without AI assistance.<\/jats:p><jats:p>Diagnostic performance of gastric neoplastic lesions without and with AI assistance was compared among 14 expert endoscopists and 12 non-expert endoscopists using an evaluation dataset consisting of 150 images containing neoplastic lesions and 350 images without lesions. A general linear mixed model was applied for comparative analysis. The primary outcome was to demonstrate superiority of sensitivity and non-inferiority of specificity among expert endoscopists using AI compared with those without AI. The significance level for sensitivity was set at 2.5% and the non-inferiority margin for specificity was defined as a log odds ratio of \u20130.25.<\/jats:p><jats:p>Our AI demonstrated superiority in sensitivity (66.4% without AI vs. 83.5% with AI; odds ratio [OR] 2.562, 97.5% confidence interval [CI] 2.069\u20133.172) and non-inferiority in specificity (90.8% without AI vs. 92.9% with AI; OR 1.326, 95% CI 1.122\u20131.565) among expert endoscopists.<\/jats:p><jats:p>AI contributed to improved diagnostic performance even among Japanese expert endoscopists in detecting gastric neoplastic lesions. These findings suggest that the AI system may have potential to support consistently high diagnostic performance across varying levels of endoscopic expertise.<\/jats:p>","DOI":"10.1055\/a-2695-0556","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T22:50:47Z","timestamp":1756939847000},"source":"Crossref","is-referenced-by-count":0,"special_numbering":"S","title":["Impact of interaction between an artificial intelligence endoscopic support system and endoscopists on diagnosis of gastric neoplastic lesions"],"prefix":"10.1055","volume":"13","clinical-trial-number":[{"clinical-trial-number":"jrct1030210697","registry":"10.18810\/jrct"}],"author":[{"given":"Hiroya","family":"Mizutani","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"},{"name":"Department of Next-Generation Endoscopic Computer Vision Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yosuke","family":"Tsuji","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"},{"name":"Department of Next-Generation Endoscopic Computer Vision Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dai","family":"Kubota","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"},{"name":"Department of Next-Generation Endoscopic Computer Vision Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroyuki","family":"Hisada","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuko","family":"Miura","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daisuke","family":"Ohki","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2746-9189","authenticated-orcid":false,"given":"Chihiro","family":"Takeuchi","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naomi","family":"Kakushima","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nobutake","family":"Yamamichi","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryosuke","family":"Kikuchi","sequence":"additional","affiliation":[{"name":"AI Medical Service Inc., Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mitsuaki","family":"Ishioka","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, The Cancer Institute Hospital Of JFCR, Koto-ku, Japan"},{"name":"Nihonbashi Ningyocho Gastroenterology and Endoscopy Clinic, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atsuo","family":"Yamada","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"},{"name":"Ochanomizu Surugadai Clinic, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinya","family":"Kodashima","sequence":"additional","affiliation":[{"name":"Department of Medicine Graduate School of Medicine, Teikyo University School of Medicine, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomohiro","family":"Tada","sequence":"additional","affiliation":[{"name":"AI Medical Service Inc., Tokyo, Japan"},{"name":"Department of Surgical Oncology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"},{"name":"Department of Gastroenterology and Proctology, Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mitsuhiro","family":"Fujishiro","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"194","published-online":{"date-parts":[[2025,10,9]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.33588","article-title":"Cancer statistics for the year 2020: An overview","author":"J Ferlay","year":"2021","journal-title":"Int J Cancer"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1097\/MEG.0000000000000657","article-title":"Missing rate for gastric cancer during upper gastrointestinal endoscopy: a systematic review and meta-analysis","volume":"28","author":"AR Pimenta-Melo","year":"2016","journal-title":"Europ J Gastroenterol Hepatol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1007\/s10120-018-0793-2","article-title":"Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images","volume":"21","author":"T Hirasawa","year":"2018","journal-title":"Gastric Cancer"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1055\/a-0855-3532","article-title":"A deep neural network improves endoscopic detection of early gastric cancer without blind spots","volume":"51","author":"L Wu","year":"2019","journal-title":"Endoscopy"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.3390\/jcm8091310","article-title":"A lesion-based convolutional neural network improves endoscopic detection and depth prediction of early gastric cancer","volume":"8","author":"HJ Yoon","year":"2019","journal-title":"J Clin Med"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"4138","DOI":"10.1109\/EMBC.2018.8513274","article-title":"Automatic detection of early gastric cancer in endoscopic images using a transferring convolutional neural network. Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference","author":"Y Sakai","year":"2018"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"e34","DOI":"10.1111\/den.13306","article-title":"Detecting gastric cancer from video images using convolutional neural networks","volume":"31","author":"M Ishioka","year":"2019","journal-title":"Digest Endosc"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1111\/jgh.15190","article-title":"Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging","volume":"36","author":"H Ueyama","year":"2021","journal-title":"J Gastroenterol Hepatol"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"7800","DOI":"10.1007\/s00464-022-09319-2","article-title":"A deep learning-based model improves diagnosis of early gastric cancer under narrow band imaging endoscopy","volume":"36","author":"D Tang","year":"2022","journal-title":"Surg Endosc"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1016\/j.gie.2020.11.014","article-title":"Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study","volume":"93","author":"H Hu","year":"2021","journal-title":"Gastrointest Endosc"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2022.101366","article-title":"Development and validation of a feature extraction-based logical anthropomorphic diagnostic system for early gastric cancer: A case-control study","volume":"46","author":"J Li","year":"2022","journal-title":"EClinicalMedicine"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/j.gie.2022.07.019","article-title":"Automatic captioning of early gastric cancer using magnification endoscopy with narrow-band imaging","volume":"96","author":"L Gong","year":"2022","journal-title":"Gastrointest Endosc"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.gie.2021.11.040","article-title":"Real-time use of artificial intelligence for diagnosing early gastric cancer by magnifying image-enhanced endoscopy: a multicenter diagnostic study (with videos)","volume":"95","author":"X He","year":"2022","journal-title":"Gastrointest Endosc"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2024.1323516","article-title":"A study on the improvement in the ability of endoscopists to diagnose gastric neoplasms using an artificial intelligence system","volume":"11","author":"B Zhang","year":"2024","journal-title":"Front Med"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2020.103146","article-title":"Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study","volume":"62","author":"D Tang","year":"2020","journal-title":"EBioMed"},{"key":"ref16","first-page":"1681","article-title":"Chronological trend in clinicopathological characteristics of gastric cancer","volume":"70","author":"M Yamada","year":"2012","journal-title":"Nihon Rinsho"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1186\/s40880-017-0234-3","article-title":"Estimates of cancer incidence and mortality in China, 2013","volume":"36","author":"R Zheng","year":"2017","journal-title":"Chinese J cancer"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7639968","article-title":"Gastric cancer screening methods: A comparative study of the chinese new gastric cancer screening score and Kyoto classification of gastritis","volume":"2022","author":"XM Liu","year":"2022","journal-title":"Gastroenterol Res Pract"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1109\/CVPR.2014.81","article-title":"Rich feature hierarchies for accurate object detection and semantic segmentation. 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA","author":"RB Girshick","year":"2014","journal-title":"IEEE"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"297","DOI":"10.2307\/1932409","article-title":"Measures of the amount of ecologic association between species","volume":"26","author":"LR Dice","year":"1945","journal-title":"Ecology"}],"container-title":["Endoscopy International Open"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2695-0556.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T22:53:07Z","timestamp":1760050387000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2695-0556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"references-count":20,"journal-issue":{"issue":"CP","published-online":{"date-parts":[[2025,1,7]]},"published-print":{"date-parts":[[2025]]}},"alternative-id":["a26950556"],"URL":"https:\/\/doi.org\/10.1055\/a-2695-0556","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["2364-3722","2196-9736"],"issn-type":[{"type":"print","value":"2364-3722"},{"type":"electronic","value":"2196-9736"}],"subject":[],"published-other":{"date-parts":[[2025,9,3]]},"published":{"date-parts":[[2025,9,3]]}}}