A Breast Cancer Detection System Using Metasurfaces With a Convolution Neural Network: A Feasibility Study
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Bibliographic record
Abstract
This work presents a breast cancer detection modality using a metasurface as the imaging medium and a microwave source. The fundamental concept is to record the electromagnetic energy, which, when transmitted through the breast, scatters differently according to the variation in the electrical properties of the breast tissue. The energy captured by the metasurface forms an impression image of the breast under test. This impression is used as a detection tool to determine the presence of a tumor inside the breast. A convolution neural network (CNN) is applied to enhance detection accuracy and provide quantitative data about tumors when present. The CNN results show the possibility of finding a tumor with a 10 mm diameter and distinguish between healthy and unhealthy breasts with 93% accuracy while determining the size and the size with location with an accuracy of 91% and 74%, respectively.
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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 | 0.001 | 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 | 0.001 | 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 it