Real-time raman spectroscopy for non-invasive skin cancer detection - preliminary results
Bibliographic record
Abstract
Raman spectroscopy is a non-invasive optical technique, which can assess molecular structures and conformations within biological tissue. The probability of Raman scattering is inherently low such that previous clinical applications of Raman spectroscopy have been limited by long data acquisition times. We have developed a rapid real-time Raman spectrometer system with measurement times of less than 1 second, paving the way for clinical application. In this presentation, we report preliminary clinical results for this real-time Raman system. To date 289 skin cancers and benign skin lesions have been measured. Using partial least squares regression and linear discriminant analysis to analyze the Raman spectra we found that skin cancers could be well differentiated from benign skin lesions (sensitivity 91% and specificity 75%) and malignant melanoma from benign pigmented lesions (sensitivity 97%, specificity 78%).
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".