ReviewDigestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society2026
World Endoscopy Organization Position Statements for Artificial Intelligence in Endoscopic Diagnosis of Gastric Epithelial Neoplasia.
Review in Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Impact of Artificial Intelligence-Assisted Endoscopy on the Detection of Upper Gastrointestinal Neoplasms: A Systematic Review and Meta-Analyses.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Pooled it
- Clinical Performance of Gastric CADe: Beyond Lesion Recognition From the G-CADe Trial.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Article
- Management of Gastric Precancerous Lesions and Early Cancer: Practice-Oriented Answers to Clinical Questions.Cancers · 2026Review
- How Does Artificial Intelligence-Assisted Endoscopy Impact Upper Gastrointestinal Screening?Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Article
- Addressing Ethical, Legal, and Social Issues on Artificial Intelligence Together With Patients' Perspectives: Prerequisites for Responsible Social Implementation in Endoscopy.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Article
- Artificial intelligence in gastric cancer research: a bibliometric and visualized analysis from 1993 to 2026.Frontiers in oncology · 2026Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The World Endoscopy Organization (WEO) has prepared position statements for artificial intelligence (AI) in endoscopic diagnosis of gastric epithelial neoplasia as part of activities in the Stomach and Duodenal Diseases Committee. Gastric cancer is still a major cause of cancer death globally, and endoscopy plays a crucial role for early detection and early treatment to improve patients' quality of life as well as to save patients' lives. Artificial intelligence (AI) is an emerging technology to have the potential to increase endoscopic diagnostic yields dramatically, but evidence in clinical use is still insufficient, only from advanced institutions in certain countries. Thus, we developed three, three, and four position statements regarding computer-aided detection, computer-aided diagnosis, and promotion of research, respectively, for better understanding of the present standpoints and future perspectives of AI in endoscopic diagnosis of gastric epithelial neoplasia. AI in the stomach must be helpful to ensure the quality of endoscopy and to increase diagnostic accuracy, but it is still controversial in terms of cost-effectiveness. In addition, it is necessary to develop AI for endoscopic diagnosis of not only gastric epithelial neoplasia but also all kinds of neoplastic lesions and the other alert lesions in the upper gastrointestinal tract in order to apply AI in the entire procedure of esophagogastroduodenoscopy (EGD). Furthermore, developing AI for risk stratification to know the best timing of EGD surveillance is warranted as future agenda.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.