Near‐infrared heating of skin to delineate non‐melanoma skin cancer lesions: A pilot study
Bibliographic record
Abstract
BACKGROUND: Surgical excision is a mainstay of treatment for non-melanoma skin cancer (NMSC); improving margin delineation can reduce the need for further monitoring/treatment. The objective of this pilot study was to determine if near-infrared radiation (NIR) application to skin causes visible changes in normal and NMSC skin, to help delineate margins. MATERIALS/METHODS: Eleven biopsy-proven NMSC lesions were included. The skin was then heated under a 175W NIR heating bulb; margins were traced onto acetate film before and after heating. Lesions were then randomly assigned to excision based on pre- or post-heating margins. Composite images were generated by overlaying the heat and no-heat lesion contours. All specimens were sent for histopathology. RESULTS: The range of closest margins in the control group was 2.0-3.0 mm with a median of 2.0 mm; the range in the intervention group was 4.0-9.0 mm with a median of 5.0 mm. Composite images showed larger heat contours when the initial lesion was larger. There was a statistically significant difference between the two groups. Overall, NIR light caused visible hyperaemia to skin, and more intense erythema to malignant skin lesions. CONCLUSION: Near-infrared light may have use in an outpatient setting for skin cancer delineation, possibly reducing the rate of positive margins.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".