Longitudinal Monitoring of Inflammatory Bowel Disease in Mice Using Endoscopic Optical Coherence Tomography
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is one of the fastest-growing diseases globally. Nearly 5 million people are affected by IBD, with an incremental growth rate of 47.45% between 1990 and 2019. AIM AND METHODS: We aim to provide a noninvasive approach to detecting IBD with an in-house developed 1310 nm endoscopic optical coherence tomography (OCT) system. Mice with acute colitis underwent a longitudinal colon imaging process for real-time and long-run disease progression. The OCT images were processed and segmented using a computer vision image processing-based segmentation algorithm for further thickness mapping and attenuation coefficient calculations. RESULT: An increase in overall colon wall thickness due to inflammation was observed, as well as a reduction in attenuation coefficient due to a change in refractive index. CONCLUSION: Comparable results with white light endoscope and histological examination suggest the clinical potential of the 1310 nm endoscopic OCT system for in vivo assessment of IBD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".