RevieweGastroenterology2024
Artificial intelligence-enabled advanced endoscopic imaging to assess deep healing in inflammatory bowel disease.
Review in eGastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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, 2 syntheses or guidelines pooled it.
- Artificial intelligence-enabled histology exhibits comparable accuracy to pathologists in assessing histological remission in ulcerative colitis: a systematic review, meta-analysis, and meta-regression.Journal of Crohn's & colitis · 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
- Advanced endoscopy and artificial intelligence-enabled vascular healing for ulcerative colitis: promising frontiers or mere mirage?Clinical endoscopy · 2026Review
- A Scoping Review of Endoscopic Assessment Considering Disease Extent in Ulcerative Colitis: Insights for the Artificial Intelligence Era.Gut and liver · 2026Article
- Current approaches to disease severity and therapy effectiveness assessment in patients with inflammatory bowel disease.World journal of gastrointestinal pharmacology and therapeutics · 2026Review
- Practices and perceptions of advanced endoscopic imaging techniques for colorectal neoplasia detection in patients with inflammatory bowel disease: report of a survey among Canadian inflammatory bowel disease specialists.iGIE : innovation, investigation and insights · 2026Article
- Comparison of Radiomics and Deep Learning Using Intestinal Ultrasound Images for Differentiating Inflammatory and Fibrotic Intestinal Strictures in Crohn's Disease.Journal of inflammation research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Endoscopic remission is the primary long-term therapeutic goal in inflammatory bowel disease (IBD). The assessment of this therapeutic target typically relies on white light endoscopy (WLE) combined with histological sampling. Nonetheless, distinguishing between endoscopic mild, patchy inflammation and quiescent disease can be challenging, and discrepancies have been observed between endoscopic and histological disease activity, mainly when using WLE. Recent advances in endoscopic technologies are gradually transforming clinical practice. Dye-based chromoendoscopy and virtual chromoendoscopy are currently available in the endoscopist armamentarium, enhancing the assessment of mucosal architecture and vascular patterns, improving the visualisation of patchy inflammation and helping detect subtle dysplastic colonic lesions. Moreover, novel advanced tools, including probe-based confocal laser endomicroscopy and endocytoscopy, offer the remarkable ability to investigate the deep aspect of the gastrointestinal tract in real time, including the structure and function of the intestinal barrier and inflammatory-related alterations. Thus, these techniques can bridge the gap between endoscopy and histology, enabling the integration of novel treat-to-target strategies associated with more favourable outcomes. Artificial intelligence (AI) represents a further step forward in overcoming the limitations associated with endoscopy, including subjectivity and the requirement for expertise. Their implementation in clinical practice may enable standardised, accurate and rapid disease assessment. Moreover, AI can aid in accurately predicting responses to therapy and disease outcomes by stratifying patients' risks, thereby advancing us towards patient-centred personalised medicine. This narrative review summarises the available advanced endoscopic technologies and their integration with AI to assess IBD activity, define promising therapeutic targets and predict long-term outcomes.
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.