{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,9]],"date-time":"2026-11-09T16:40:49Z","timestamp":1794242449639,"version":"4.9.0"},"reference-count":30,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Gastro and Hepatol"],"published-print":{"date-parts":[[2022,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aim<\/jats:title>\n                    <jats:p>Contrast\u2010enhanced harmonic endoscopic ultrasonography (CH\u2010EUS) is useful for the diagnosis of lesions inside and outside the digestive tract. This study evaluated the value of artificial intelligence (AI) in the diagnosis of gastric submucosal tumors by CH\u2010EUS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective study included 53 patients with gastrointestinal stromal tumors (GISTs) and leiomyomas, all of whom underwent CH\u2010EUS between June 2015 and February 2020. A novel technology, SiamMask, was used to track and trim the lesions in CH\u2010EUS videos. CH\u2010EUS was evaluated by AI using deep learning involving a residual neural network and leave\u2010one\u2010out cross\u2010validation. The diagnostic accuracy of AI in discriminating between GISTs and leiomyomas was assessed and compared with that of blind reading by two expert endosonographers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of the 53 patients, 42 had GISTs and 11 had leiomyomas. Mean tumor size was 26.4\u00a0mm. The consistency rate of the segment range of the tumor image extracted by SiamMask and marked by the endosonographer was 96% with a Dice coefficient. The sensitivity, specificity, and accuracy of AI in diagnosing GIST were 90.5%, 90.9%, and 90.6%, respectively, whereas those of blind reading were 90.5%, 81.8%, and 88.7%, respectively (\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.683). The\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.med.osaka-u.ac.jp\/pub\/kid\/clinicaljournalclub12.html\">\u03ba<\/jats:ext-link>\n                      coefficient between the two reviewers was 0.713.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The diagnostic ability of CH\u2010EUS results evaluated by AI to distinguish between GISTs and leiomyomas was comparable with that of blind reading by expert endosonographers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jgh.15780","type":"journal-article","created":{"date-parts":[[2022,1,18]],"date-time":"2022-01-18T20:18:45Z","timestamp":1642537125000},"page":"841-846","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Value of artificial intelligence with novel tumor tracking technology in the diagnosis of gastric submucosal tumors by contrast\u2010enhanced harmonic endoscopic ultrasonography"],"prefix":"10.1111","volume":"37","author":[{"given":"Hidekazu","family":"Tanaka","sequence":"first","affiliation":[{"name":"Department of Gastroenterology and Hepatology Kindai University Hospital  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1568-0769","authenticated-orcid":false,"given":"Ken","family":"Kamata","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology and Hepatology Kindai University Hospital  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rika","family":"Ishihara","sequence":"additional","affiliation":[{"name":"Department of Informatics Kindai University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hisashi","family":"Handa","sequence":"additional","affiliation":[{"name":"Department 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