Polarization speckle imaging as a potential technique for<i>in vivo</i>skin cancer detection
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
Skin cancer is the most common cancer in the Western world. In order to accurately detect the disease, especially malignant melanoma-the most fatal form of skin cancer-at an early stage when the prognosis is excellent, there is an urgent need to develop noninvasive early detection methods. We believe that polarization speckle patterns, defined as a spatial distribution of depolarization ratio of traditional speckle patterns, can be an important tool for skin cancer detection. To demonstrate our technique, we conduct a large in vivo clinical study of 214 skin lesions, and show that statistical moments of the polarization speckle pattern could differentiate different types of skin lesions, including three common types of skin cancers, malignant melanoma, squamous cell carcinoma, basal cell carcinoma, and two benign lesions, melanocytic nevus and seborrheic keratoses. In particular, the fourth order moment achieves better or similar sensitivity and specificity than many well-known and accepted optical techniques used to differentiate melanoma and seborrheic keratosis.
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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 | 0.000 | 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