Time Domain Analysis of UWB Breast Cancer Detection
Bibliographic record
Abstract
Recently, there has been considerable effort to investigate ultra-wideband (UWB) technology for the purpose of breast cancer detection. Previous publications based on frequency sweep have shown that UWB imaging systems have the potential to detect small sized (less than 2 cm) tumors. This work provides measurement results of a UWB breast cancer detection system consisting of a pulse generator, wideband oscilloscope, and two compact ultra-wideband antennas. The antenna experimental results show that the return loss is below -10 dB from 3.4 GHz to 10 GHz. The backscattered signal from tumor stimulant is measured and used to perform detection experiments. An autoregressive (AR) model is used to extract the energy of signal from the noise background and to perform the detection. The comparable detection rate with mammography quantifies the feasibility of UWB breast cancer detection. The advantage of this work is that it experimentally shows the potential of a time domain processing UWB system to detect early breast cancer tumor and paves the way for future work
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".