Evidence map›Paper›PMID 41948841›Full record

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.

Mitsuhiro Fujishiro, Naomi Kakushima, Seiichiro Abe, Hon Chi Yip, Xuemei Liu, Gwan Ha Kim, Mathieu Pioche, George Adel Cortas, Kazuki Sumiyama, Vitor Nunes Arantes and 2 more

Abstract readReviewConsensus Statement
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Clinical Performance of Gastric CADe: Beyond Lesion Recognition From the G-CADe Trial.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026
    Article
  3. Review
  4. How Does Artificial Intelligence-Assisted Endoscopy Impact Upper Gastrointestinal Screening?Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026
    Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Mitsuhiro FujishiroDepartment of Gastroenterology in Organ Pathophysiology Program, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-4074-1140
Naomi KakushimaDepartment of Gastroenterology in Organ Pathophysiology Program, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Seiichiro AbeEndoscopy Division, National Cancer Center Hospital, Tokyo, Japan.
Hon Chi YipDivision of Upper GI and Metabolic Surgery, Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Xuemei LiuDepartment of Gastroenterology, Digestive Disease Hospital, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Gwan Ha KimDepartment of Internal Medicine, Pusan National University College of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Korea.
Mathieu PiocheHepatogastroenterology Division, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France.
George Adel CortasSaint George Hospital University Medical Center, Faculty of Medicine, University of Balamand Beirut, Beirut, Lebanon.
Kazuki SumiyamaDepartment of Endoscopy, School of Medicine, The Jikei University, Tokyo, Japan.
Vitor Nunes ArantesEndoscopy Unit, Alfa Institute of Gastroenterology, School of Medicine, Federal University of Minas Gerais, Hospital Mater Dei Contorno, Belo Horizonte, Brazil.
Fabian EmuraDigestive Health and Liver Diseases, Miller School of Medicine, University of Miami, Coral Gables, Florida, USA.
Mário Dinis-RibeiroDepartment of Gastroenterology, Portuguese Institute of Oncology of Porto, Porto, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceDiagnosis, Computer-AssistedGastroscopyStomach NeoplasmsHumansartificial intelligenceearly gastric cancerendoscopic diagnosisWorld Endoscopy Organization

Identifiers

PMID41948841
PMCPMC13058774

What OpenQuestion holds

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Registered trials

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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.