ReviewGastroenterology research and practice2023
Artificial Intelligence in Inflammatory Bowel Disease Endoscopy: Advanced Development and New Horizons.
Review in Gastroenterology research and practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 19 citations in OpenAlex.
- Optimized computer-assisted technique for increasing adenoma detection during colonoscopy: a randomized controlled trial.Surgical endoscopy · 2025Trial
- Subclass-Aware Contrastive Semi-Supervised Learning for Inflammatory Bowel Disease Classification from Colonoscopy Images.Bioengineering (Basel, Switzerland) · 2025Article
- Interpretable Artificial Neural Network Models for Predicting Anti-Adalimumab Immune Complex and Serum Drug Level in Crohn's Disease: A Proof-of-Concept Study.Pharmaceutics · 2025Article
- Artificial intelligence in inflammatory bowel disease.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association · 2025Review
- Current Approaches to Ulcerative Colitis Management: A Comprehensive Overview of Methodologies and Treatments.Infectious disorders drug targets · 2025Review
- 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
- The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.Diagnostics (Basel, Switzerland) · 2024Review
- Managing Ulcerative Colitis and Crohn's Disease: Should the Target Be Endoscopy, Histology, or Both?Journal of the Canadian Association of Gastroenterology · 2024Article
- Advancements in the use of AI in the diagnosis and management of inflammatory bowel disease.Frontiers in robotics and AI · 2024Review
- Deep learning and minimally invasive inflammatory activity assessment: a proof-of-concept study for development and score correlation of a panendoscopy convolutional network.Therapeutic advances in gastroenterology · 2024Article
- Impact of an Educational Mobile App on Inflammatory Bowel Disease Colonoscopy Report Quality.Digestive diseases and sciences · 2023Article
- Next-Generation Endoscopy in Inflammatory Bowel Disease.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inflammatory bowel disease (IBD) is a complex chronic immune disease with two subtypes: Crohn's disease and ulcerative colitis. Considering the differences in pathogenesis, etiology, clinical presentation, and response to therapy among patients, gastroenterologists mainly rely on endoscopy to diagnose and treat IBD during clinical practice. However, as exemplified by the increasingly comprehensive ulcerative colitis endoscopic scoring system, the endoscopic diagnosis, evaluation, and treatment of IBD still rely on the subjective manipulation and judgment of endoscopists. In recent years, the use of artificial intelligence (AI) has grown substantially in various medical fields, and an increasing number of studies have investigated the use of this emerging technology in the field of gastroenterology. Clinical applications of AI have focused on IBD pathogenesis, etiology, diagnosis, and patient prognosis. Large-scale datasets offer tremendous utility in the development of novel tools to address the unmet clinical and practice needs for treating patients with IBD. However, significant differences among AI methodologies, datasets, and clinical findings limit the incorporation of AI technology into clinical practice. In this review, we discuss practical AI applications in the diagnosis of IBD via gastroenteroscopy and speculate regarding a future in which AI technology provides value for the diagnosis and treatment of IBD patients.
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.