ArticleUnited European gastroenterology journal2025
Prospective Evaluation of Real-Time Artificial Intelligence for the Hill Classification of the Gastroesophageal Junction.
Article in United European gastroenterology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06040723 (Real Time Determination of the Hill Grade During Gastroscopy Using Artificial Intelligence), which is not on this map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Real Time Determination of the Hill Grade During Gastroscopy Using Artificial Intelligence
Who cites it
6 citing papers in PubMed.
- A prospective study evaluating an artificial intelligence-based system for withdrawal time measurement.Endoscopy · 2026Trial
- Patterns of AI Use in Clinical Work by Hospitalists: Survey Study.Journal of medical Internet research · 2026Article
- The American Foregut Society endoscopic classification outperforms Hill in phenotyping the esophago-gastric junction to guide gastroesophageal reflux disease management.Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus · 2026Article
- The "ABCD" framework for assessment: a task-oriented approach to reconcile multimodal diagnostic discordance.Frontiers in medicine · 2026Review
- Ascending the "Hill" of Artificial Intelligence in Upper Gastrointestinal Endoscopy.United European gastroenterology journal · 2025Article
- Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images.PloS one · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundAssessment of the gastroesophageal junction (GEJ) is an integral part of gastroscopy; however, the absence of standardized reporting hinders consistency of examination documentation. The Hill classification offers a standardized approach for evaluating the GEJ. This study aims to compare the accuracy of an artificial intelligence (AI) system with that of physicians in classifying the GEJ according to Hill in a prospective, blinded, superiority trial.
methodsConsecutive patients scheduled for gastroscopy with an intact GEJ were recruited during clinical routine from October 2023 to December 2023. Nine physicians (six experienced, three inexperienced) assessed the Hill grade, and the AI system operated in the background in real-time. The gold standard was determined by a majority vote of independent assessments by three expert endoscopists who did not participate in the study. The primary outcome was accuracy. Secondary outcomes were per-Hill grade analysis and result comparison for experienced and inexperienced endoscopists separately.
resultsIn 131 analysed examinations the AI's accuracy of 84.7% (95% CI: 78.6-90.8) was significantly higher than 62.5% (95% CI: 54.2-71) of physicians (p < 0.01). The AI outperformed physicians in all but one cases in the per-Hill-class analysis. AI was significantly more accurate than inexperienced physicians (85% vs. 56%, p < 0.01) and in trend better than experienced physicians (84% vs. 69.6%, p = 0.07).
conclusionsAI was significantly more accurate than examiners in assessing the Hill classification. This superior model performance can prove beneficial for endoscopists, especially those with limited experience.
trial registrationClinicalTrials.gov identifier: NCT06040723.
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