Artificial intelligence-assisted upper gastrointestinal endoscopy for neoplasm detection: Systematic review and meta-analysis of randomized controlled trials

BACKGROUNDEsophagogastroduodenoscopy is operator-dependent, and early upper gastrointestinal neoplasms are frequently missed.Although randomized trials and a previous metaanalysis have reported that real-time artificial intelligence (AI) improves neoplasm detection, the first large multicenter trial with centralized pathology adjudication found no significant benefit for gastric neoplasms.Furthermore, the pooled evidence has not been reassessed following publication of this trial. AIMTo reappraise whether AI-assisted endoscopy increases per-patient neoplasm detection overall and by anatomical site. METHODSFollowing a registered protocol (PROSPERO CRD420261424675), we searched PubMed, EMBASE, and Cochrane Library through June 2026 and two Chinese-language databases through September 2026 for randomized trials comparing conventional and real-time AI-assisted endoscopy in adults.Risk of bias (RoB) and certainty of evidence were assessed using the RoB 2 tool and GRADE rating.Effects were pooled in Python using restricted maximum-likelihood random-effects models with Hartung-Knapp-Sidik-Jonkman confidence intervals (CIs).Prediction intervals were calculated, with sensitivity analyses by anatomical target and system functionality. RESULTSFourteen randomized trials (90828 participants) were included.AI increased per-patient detection of upper gastrointestinal neoplasms [10 trials; risk ratio (RR): 1.47, 95%CI:1.25-1.73;I 2 = 40%; prediction interval 1.04-2.09;moderate certainty], with similar 4/51 esophageal (RR: 1.61, 95%CI: 1.27-2.03;I 2 = 0%; moderate certainty) and gastric (RR:1.45, 95%CI: 1.11-1.89;I 2 = 60%; low certainty; subgroup P = 0.50) estimates and no variation by system functionality.Patient-level premalignant lesion detection increased (4 trials; RR: 1.80, 95%CI: 1.09-2.96),early cancer detection was imprecise (6 trials; RR:1.28, 95%CI: 0.86-1.91),and the lesion-level miss rate was lower with AI (RR: 0.21, 95%CI: 0.09-0.49).Adverse events did not differ; heterogeneous procedural outcomes were synthesized narratively.The largest, centrally adjudicated trial drove the gastric heterogeneity. CONCLUSION AI-assisted endoscopy increases upper gastrointestinal neoplasm detection in Asiantrial settings, although the evidence for gastric neoplasia remains heterogeneous and of low certainty.Further confirmatory trials with patient-important endpoints are warranted.