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Record W2028527352 · doi:10.1109/biocas.2014.6981745

A fully integrated telemonitoring system for diagnosing in-stent restenosis

2014· article· en· W2028527352 on OpenAlexaff
Kamyar Keikhosravy, Pouya Kamalinejad, Leila Keikhosravy, Arash Zargaran-Yazd, Kenichi Takahata, Shahriar Mirabbasi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRestenosisTransmitterVoltageStentCMOSSensitivity (control systems)Pressure sensorComputer scienceWirelessElectrical engineeringElectronic engineeringEngineeringTelecommunicationsMedicineChannel (broadcasting)Radiology

Abstract

fetched live from OpenAlex

This paper presents a fully integrated monitoring system for diagnosing restenosis in coronary-artery stents. Power is transferred wirelessly to the 0.13-μm CMOS monitoring circuit that is embedded on the stent and reads and transmits the sensory data from the pressure sensors which are also embedded on the stent. An auxiliary circuit is introduced to facilitate the alignment of the external reader with the stent. The alignment circuit starts operating from a rectified supply of 500 mV drawing 8.3 μA from the harvested supply voltage. The main transmitter which sends the sensory data operates from a rectified supply voltage of 880 mV while drawing ≈178 μA. The monitoring system provides a sensitivity of 555 kHz/fF. In-vitro measurement results confirm the performance of the system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.009
GPT teacher head0.198
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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