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Welcome to the Artificial Intelligence in Gastrointestinal Endoscopy
Multimodal artificial intelligence in capsule endoscopy: Integrating video and sensor data for advanced gastrointestinal diagnostics
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Artificial Intelligence in Gastrointestinal Endoscopy is a rigorously peer-reviewed, open-access academic journal dedicated to publishing original, high-quality research findings in the field of gastrointestinal endoscopy, including clinical, translational, and basic studies, as well as research involving artificial intelligence. The journal focuses on, but is not limited to, the following areas: Capsule endoscopy, colonoscopy, double-balloon enteroscopy, duodenoscopy, endoscopic retrograde cholangiopancreatography, endosonography, esophagoscopy, gastrointestinal endoscopy, gastroscopy, laparoscopy, natural orifice endoscopic surgery, proctoscopy, and sigmoidoscopy. Types of articles published by the journal include clinical study, basic study, case report, editorial, review, minireview, systematic review, meta-analysis, guidelines, and correspondence.  The journal sincerely welcomes experts and scholars to submit original research manuscripts. Each submission will be reviewed by at least two independent referees, who will critically assess its novelty, significance, and reproducibility, as well as any flaws in experimental design and data processing, in order to provide authors with meaningful peer review reports. The journal adheres to editorial policies, peer-review processes, editorial processes, and publication ethics guidelines developed by the editorial office in accordance with the Committee on Publication Ethics, the International Committee of Medical Journal Editors, and the World Association of Medical Editors. By doing so, the journal strives to provide authors with high-quality services, offer readers high-quality academic content, and further advance clinical practice. Submit an Article >>

2026 Published Issues
1
Editors-in-Chief
  • Krish Ragunath, MD, Professor, (Email: krish.ragunath@curtin.edu.au) Department of Gastroenterology and Hepatology, Royal Perth Hospital, Perth WA6000, Australia
Indexing/Abstracting
The AIGE is now abstracted and indexed in Reference Citation Analysis, China Science and Technology Journal Database.
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There is currently no impact factor.
ISSN
2689-7164 (online)
Latest Manuscript Statistics
Received (77), Duration of Peer Review (13 days/Mean), Days from Submission to First Decision (32 days/Mean), Second Decision Time (28 days/Mean), Accepted (63.6%/Mean), Production Time (25 days/Mean), Time to Publication (99 days/Mean), and Rejected (18.2%/Mean).
Current Issue
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Contents Volume 7 Issue 1 March 8, 2026
Minireviews
Artificial intelligence in upper gastrointestinal bleeding: Can machine learning predict endotherapy requirements? 
Prakash Kumar Sasmal, Manas Kumar Panigrahi, S Rakesh Kumar 
Artif Intell Gastrointest Endosc 7(1):114426. Published online Mar 8, 2026. doi: 10.37126/aige.v7.i1.114426
Multimodal artificial intelligence in capsule endoscopy: Integrating video and sensor data for advanced gastrointestinal diagnostics 
Omesh Goyal, Manjeet Kumar Goyal, Ashita Rukmini Vuthaluru, Varna Taranikanti, Kirti Arora, Rahul Chowdhary, Chirag Vohra, Chitresh Kapadia, Insiya Mohammed Rampurawala, Param Darpan Sheth, Rishi Chowdhary 
Artif Intell Gastrointest Endosc 7(1):117988. Published online Mar 8, 2026. doi: 10.37126/aige.v7.i1.117988
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