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Record W2281421890 · doi:10.1109/tbme.2015.2465867

An Early Clinical Study of Time-Domain Microwave Radar for Breast Health Monitoring

2015· article· en· W2281421890 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrowave imagingRadarMicrowaveTime domainNoise (video)Radar imagingMedicineMedical physicsBiomedical engineeringRemote sensingComputer scienceTelecommunicationsArtificial intelligenceComputer visionGeology

Abstract

fetched live from OpenAlex

This study reports on monthly scans of healthy patient volunteers with the clinical prototype of a microwave imaging system. The system uses time-domain measurements, and incorporates a multistatic radar approach to imaging. It operates in the 2-4 GHz range and contains 16 wideband sensors embedded in a hemispherical dielectric radome. The system has been previously tested on tissue phantoms in controlled experiments. With this system prototype, we scanned 13 patients (26 breasts) over an eight-month period, collecting a total of 342 breast scans. The goal of the study described in this paper was to investigate how the system measurements are impacted by multiple factors that are unavoidable in monthly monitoring of human subjects. These factors include both biological variability (e.g., tissue variations due to hormonal changes or weight gain) and measurement variability (e.g., inconsistencies in patient positioning, system noise). For each patient breast, we process the results of the monthly scans to assess the variability in both the raw measured signals and in the generated images. The significance of this study is that it quantifies how much variability should be anticipated when conducting microwave breast imaging of a healthy patient over a longer period. This is an important step toward establishing the feasibility of the microwave radar imaging system for frequent monitoring of breast health.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.293
Teacher spread0.268 · 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