Modeling wavelength dependence of laser tumor hyperthermic treatments
Bibliographic record
Abstract
Breast cancer is the world's most prevalent cancer, with roughly 1 in 16 Americans being diagnosed within their lifetime. One form of treatment for breast cancer is hyperthermal therapy, which involves heating cancer tumors to between 43-50 °C to cause apoptosis and above 50 °C for necrosis. Lasers are an effective method to raise the temperature of tumors for apoptosis and necrosis. However, to date, no study has compared the efficiency of visible, near infrared and mid infrared lasers for hyperthermal treatments. Here, we present a finite element model simulation using COMSOL Multiphysics to compare hyperthermal therapy using 500 nm, 900 nm, 3 μm and 10 μm laser sources using a fiber optic delivery system. Our results indicate that mid-infrared lasers result in shorter treatment times, while near infrared wavelengths likely result in less healthy tissue damage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".