ReviewDigestive diseases and sciences2025
Integration of Artificial Intelligence-Enhanced Capsule Endoscopy in Clinical Practice: A Review of Market-Available Tools for Clinical Practice.
Review in Digestive diseases and sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Optimizing multiple diagnostic modalities for small bowel evaluation: a strategic approach.The Korean journal of internal medicine · 2026Review
- Artificial Intelligence for the Detection of Small Bowel Lesions and Neoplasia: A Scoping Review.Cureus · 2026Review
- New Technologies for IBD Endoscopy.Journal of clinical medicine · 2026Review
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- Artificial Intelligence-Based Localization of Small Bowel Anatomic Transition Zones in Crohn's Disease Using Capsule Endoscopy.Endoscopy international open · 2026Article
- Artificial Intelligence in Gastrointestinal Endoscopy: Current Advances, Clinical Integration, and Future Directions: A Narrative Review.Clinical and experimental gastroenterology · 2026Review
- Advances in pediatric video capsule endoscopy: current applications and future directions.Frontiers in pediatrics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence (AI) into capsule endoscopy is transforming gastrointestinal diagnostics by enhancing lesion detection and optimizing reading efficiency. This review focuses on the clinical applications of commercially available AI-powered capsule endoscopy systems, particularly for small bowel evaluation. Recent clinical trials and observational studies are analyzed to assess the diagnostic performance, practical benefits, and limitations of these systems. Additionally, key challenges related to standardization, data quality, and clinical validation are discussed. Currently available AI systems significantly reduce reading times and demonstrate high detection capabilities, depending on the algorithm and device used. However, a substantial number of lesions remain undetected, preventing full reliance on these tools. Future advancements must focus on improving detection rates and validating the clinical relevance of missed lesions. Additionally, standardizing AI algorithms across different capsule systems is essential to ensure consistency, reliability, and broader clinical adoption. Establishing homologation frameworks will be key to achieving uniform performance and seamless integration into routine practice.
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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.