On the use of smart stents for monitoring in-stent restenosis
Bibliographic record
Abstract
In angioplasty with stent placement, re-narrowing of the artery within the stent site may occur due to the body's natural response to "heal" the stented area. This re-narrowing, also known as "in-stent restenosis", usually occurs within 6 months after surgery. To monitor and diagnose in-stent restenosis, passive telemonitoring using smart stents has been already proposed. In this paper, we present a feasibility study and advocate the use of an alternative method, namely active telemonitoring, which uses an integrated circuit embedded on the smart stent. Electromagnetic simulations and in-vitro measurements are presented to find the suitable range of frequency to wirelessly transfer power to the active device embedded on the smart stent. Furthermore, the range of induced power levels are simulated and experimentally verified.
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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".