ReviewGastroenterology2025
Artificial Intelligence-Enabled Clinical Trials in Inflammatory Bowel Disease: Automating and Enhancing Disease Assessment and Study Management.
Review in Gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Healthcare Providers' Perspectives on the Role of Artificial Intelligence in the Care of Patients with Inflammatory Bowel Disease: An International Survey.Digestive diseases and sciences · 2026Article
- Automated AI-based Mayo Endoscopic Scoring for ulcerative colitis across adult and pediatric cohorts from diverse populations.Journal of Crohn's & colitis · 2026Article
- Artificial intelligence in inflammatory bowel disease: From current evidence, clinical translation, and the road to precision medicine.Chinese medical journal · 2026Review
- Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact.Nature reviews. Gastroenterology & hepatology · 2026Review
- Artificial intelligence detection of endoscopic moderate-to-severe ulcerative colitis: a novel tool to enhance clinical trial recruitment.iGIE : innovation, investigation and insights · 2026Article
- Recent Advances in Artificial Intelligence for Endoscopic and Multimodal Assessment of Inflammatory Bowel Disease: A Review.International journal of general medicine · 2026Review
- Use of Modified YOLOv5 Algorithm in the Differential Diagnosis of Colonic Crohn's Disease and Ulcerative Colitis on CTE Images.Gastroenterology research and practice · 2025Article
- Article
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
Abstract
Artificial intelligence (AI) will fundamentally improve how we perform clinical trials by addressing issues of standardizing disease scoring, improving the sensitivity and precision of activity and phenotype assessments, and automating laborious and time-consuming study functions. Progress in AI image analysis is quickly proving to replicate expert judgment in endoscopy, histology, and cross-sectional imaging with speed, reproducibility, and reduced bias. However, AI analytics offer the ability to quantify disease characteristics with more detail and precision than human experts. Large language models and generative AI are automating the collection of high-quality data from electronic records and improving our ability to predict patient outcomes. This narrative review will focus on AI tools available today, their expected implementation, and future-facing opportunities for AI to reimagine inflammatory bowel disease clinical trials.
Indexed as
Identifiers
What OpenQuestion holds
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.