ReviewGastroenterology2022
Artificial Intelligence for Disease Assessment in Inflammatory Bowel Disease: How Will it Change Our Practice?
Review in Gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06457035 (Development and Validation of a Nomogram for Predicting Surgery in Newly-diagnosed Crohn's Disease), which is not on this map. Cited by 57 papers, 2 of them syntheses that pooled 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.
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.
Development and Validation of a Nomogram for Predicting Surgery in Newly-diagnosed Crohn's Disease: a Retrospective Cohort Study
Who cites it
57 citing papers in PubMed, 2 syntheses or guidelines pooled it, 99 citations in OpenAlex.
- The Effectiveness of Medical Therapies for Joint, Skin and Eye Extraintestinal Manifestations in IBD-An Umbrella Review.Alimentary pharmacology & therapeutics · 2025Pooled it
- The global academic distribution and changes in research hotspots of artificial intelligence in inflammatory bowel disease since 2000.Frontiers in medicine · 2025Pooled it
- 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
- Agentic artificial intelligence in inflammatory bowel disease: toward autonomous and adaptive care.Crohn's & colitis 360 · 2026Article
- Deep Learning-Based Objective Quantification of Nasopharyngeal Endoscopic Findings for Standardized Assessment of Inflammation.Diagnostics (Basel, Switzerland) · 2026Article
- Current approaches to disease severity and therapy effectiveness assessment in patients with inflammatory bowel disease.World journal of gastrointestinal pharmacology and therapeutics · 2026Review
- Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact.Nature reviews. Gastroenterology & hepatology · 2026Review
- Artificial intelligence and digital transformation of gastroenterology and hepatology: A critical review of clinical applications and future challenges.World journal of hepatology · 2026Review
- Progress in fully automated abdominal CT interpretation-an update over the past decade.Abdominal radiology (New York) · 2026Review
- Role of MRI radiomics in deep learning-based prediction of intestinal diseases.International journal of colorectal disease · 2026Review
- Deep learning-based quantitative histopathology of endoscopic biopsies in Crohn's disease: a retrospective cross-sectional validation study.Frontiers in immunology · 2026Article
- Switching Between Anti-TNFs and Other Biologic Drugs in Paediatric Inflammatory Bowel Disease: A Narrative Review and Practical Clinical Guide.Journal of inflammation research · 2026Review
- Preventing relapse in ulcerative colitis remission maintenance: machine learning prediction and reinforcement-learning herbal prescription optimization with external validation.Frontiers in medicine · 2026Article
- Integrated structural and functional brain imaging reveals biomarkers of disease activity in Crohn's disease.BMC gastroenterology · 2025Article
- Review
- Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges.World journal of gastroenterology · 2025Article
- Artificial intelligence in inflammatory bowel disease: Current applications and future directions.World journal of gastroenterology · 2025Review
- Prospects of AI-Powered Bowel Sound Analytics for Diagnosis, Characterization, and Treatment Management of Inflammatory Bowel Disease.Medical sciences (Basel, Switzerland) · 2025Review
- The Role of Imaging in Inflammatory Bowel Diseases: From Diagnosis to Individualized Therapy.Diagnostics (Basel, Switzerland) · 2025Review
- Roles of intestinal stem cells in inflammatory bowel disease pathogenesis.World journal of stem cells · 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
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Artificial intelligence (AI) has arrived and it will directly impact how we assess, monitor, and manage inflammatory bowel disease (IBD). Advances in the machine learning methodologies that power AI have produced astounding results for replicating expert judgment and predicting clinical outcomes, particularly in the analysis of imaging. This review will cover general concepts for AI in IBD, with descriptions of common machine learning methods, including decision trees and neural networks. Applications of AI in IBD will cover recent achievements in endoscopic image interpretation and scoring, new capabilities for cross-sectional image analysis, natural language processing for automated understanding of clinical text, and progress in AI-powered clinical decision support tools. In addition to detailing current evidence supporting the capabilities of AI for replicating expert clinical judgment, speculative commentary on how AI may advance concepts of disease activity assessment, care pathways, and pathophysiologic mechanisms of IBD will be addressed.
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.