Real‐time use of a computer‐aided system for polyp detection during colonoscopy, an ambispective study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate ambispectively the effectiveness of a real-time computer-aided detection (CADe) system on the number of polyp (PPC) or adenoma per colonoscopy (APC), and polyp (PDR) or adenoma detection rate (ADR). METHODS: Eight-five videos marked using the CADe system, together with the unmarked videos, were reviewed by two senior endoscopists. Polyps detected in the marked and unmarked videos were recounted in parallel. Additionally, 128 consecutive patients were enrolled for a prospective evaluation using a standard colonoscopy or the CADe monitor alternately every 2 weeks. The PC, APC, PDR and ADR were compared between the two groups. RESULTS: The total number of polyps reported in the unmarked and marked videos were 73 and 88, respectively (mean PPC 0.86 vs 1.04, P = 0.001). The proportion of polyps detected per colonoscopy increased by 20.5%. Of the 128 prospectively enrolled patients, 186 polyps were detected. The mean PPC was higher in the CADe colonoscopy than in the standard colonoscopy (1.66 vs 1.13, P = 0.039). The PDR using the CADe colonoscopy was significantly higher than that of the standard colonoscopy (78.1% vs 56.3%, P = 0.008). CONCLUSION: Real-time CADe system significantly increases the PDR and PPC under the situation of a high rate of polyp detection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".