Advances in endoscopy in IBD diagnostics and management
Bibliographic record
Abstract
Endoscopy remains an essential modality for the diagnosis, risk stratification, monitoring, and therapy of inflammatory bowel disease (IBD). Recent advances, including high-definition imaging, dye-based and virtual chromoendoscopy, and AI-assisted interpretation, improve dysplasia detection and grading of inflammatory activity, enabling treat-to-target care. In Crohn's disease, small-bowel and pan-enteric capsule endoscopy expand noninvasive assessment, while device-assisted enteroscopy allows targeted biopsy and therapy when tissue or intervention is required. Standardized scoring systems (MES/UCEIS, SES-CD, Rutgeerts) support objective follow-up, including early postoperative evaluation. Therapeutically, endoscopic balloon dilation for short strictures and advanced resection techniques (EMR/ESD) for visible dysplasia in experienced centers provide organ-sparing options; endoscopic fistula closure remains investigational. This review synthesizes contemporary trials and ECCO, ESGE, and ASGE guidance into practical algorithms that promote precise surveillance and timely intervention, positioning endoscopy as a functional, predictive, and increasingly personalized tool in IBD care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".