Improving the Diagnostic Capability of Microwave Radar Imaging Systems using Machine Learning
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.
Bibliographic record
Abstract
Breast microwave sensing (BMS) is a potential breast cancer detection technique that uses low-power microwave radiation to detect the presence of cancerous lesions. This work presents the results of the application of a multilayer perceptron (MLP) and support vector machine with radial basis function (SVM RBF) to breast cancer detection for a portable BMS prototype. Numerical 2D phantoms belonging to either BI-RADS Class 1 or Class 2 classifications were used to produce simulated data as collected by the portable system using an array of twelve sensors operating at five frequencies between 2.3 GHz and 6.5 GHz. Five feature preprocessing pipelines and their impact on classification performance were evaluated. An area under the curve of the receiver operating curve (ROC AUC) as high as (95 ± 1)% for BI-RADS Class 1 and as high as (94 ± 1)% for BI-RADS Class 2 were obtained using the SVM RBF, and as high as (94 ± 1)% for Class 1 and (92 ± 2)% for Class 2 using the MLP.
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 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 | 0.000 | 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 it