Applications of visible near-infrared spectroscopy and imaging in burn injury assessment
Bibliographic record
Abstract
The major objective of the project is to develop a noninvasive method to assess thermal burns. Currently, the diagnosis relies primarily upon visual assessment of the injury by a burn specialist and/or plastic surgeon. The diagnosis is based on the surface appearance of the wound to determine the type or depth of the burn. Near IR spectroscopic measurements of injured tissue provide an objective means of distinguishing between surface and subsurface changes related to the tissue injury. An acute porcine model is employed to investigate the potential of near IR spectroscopy to accurately distinguish between burns of varying severity in the early postburn period. Parallel factor analysis is used to investigate the spectral changes related to burns of varying severity. Burn injuries drastically alter the physical and optical properties of the tissue. Thermal destruction of cutaneous vasculature disrupts perfusion and oxygen delivery to the affected tissue. Tissue blood oxygenation decreases with increased severity of the burn. The result demonstrate that near IR spectroscopy may provide a new tool for objective clinical assessment of burn injuries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".