{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T06:19:57Z","timestamp":1787638797072,"version":"build-2736575974"},"reference-count":42,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82370524"],"award-info":[{"award-number":["82370524"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010029","name":"Taishan Scholar Foundation of Shandong Province","doi-asserted-by":"publisher","award":["tsqn202408340"],"award-info":[{"award-number":["tsqn202408340"]}],"id":[{"id":"10.13039\/501100010029","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Digestive Endoscopy"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Early detection of upper gastrointestinal (UGI) neoplasms is challenging because of their subtle endoscopic features. Artificial intelligence (AI) has improved endoscopic imaging and lesion recognition. This meta\u2010analysis aimed to assess the effectiveness of AI\u2010assisted real\u2010time esophagogastroduodenoscopy (EGD) for detecting UGI neoplasms based on evidence from randomized controlled trials (RCTs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>PubMed, EMBASE, and Cochrane Library were searched for RCTs comparing AI\u2010assisted EGD with conventional EGD up to April 11, 2026. Risk ratios (RRs) were calculated for the neoplasm detection rate (DR), and incidence rate ratios (IRRs) were pooled for lesions per endoscopy (LPE). Subgroup analyses were conducted according to AI system and pathological types. Random\u2010effects models with Hartung\u2013Knapp adjustment were applied.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Ten RCTs involving 87,721 participants were included. Compared with conventional EGD, AI\u2010assisted EGD significantly improved neoplasm DRs in the esophagus (RR\u2009=\u20091.47, 95% confidence interval [CI] 1.13\u20131.90,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.012) and stomach (RR\u2009=\u20091.47, 95% CI 1.02\u20132.13,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.043). In subgroup analyses, computer\u2010assisted detection (CADe) was associated with increased LPE of esophageal neoplasms (IRR\u2009=\u20091.62, 95% CI 1.08\u20132.45,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.033). AI\u2010assisted EGD also increased the LPEs of gastric cancer (IRR\u2009=\u20091.45, 95% CI 1.09\u20131.92,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.022) and low\u2010grade intraepithelial neoplasia (IRR\u2009=\u20091.39, 95% CI 1.13\u20131.70,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.012).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI\u2010assisted real\u2010time EGD was associated with improved detection of UGI neoplasms and may support endoscopists in routine clinical practice. Further studies are required to evaluate the effectiveness of different AI systems across pathological subtypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>PROSPERO; CRD420251158943<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/den.70268","type":"journal-article","created":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T04:59:51Z","timestamp":1787374791000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Impact of Artificial Intelligence\u2010Assisted Endoscopy on the Detection of Upper Gastrointestinal Neoplasms: A Systematic Review and Meta\u2010Analyses"],"prefix":"10.1111","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-8794-8730","authenticated-orcid":false,"given":"Mingru","family":"Liu","sequence":"first","affiliation":[{"name":"Department of 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