The non-invasive diagnostic modality for the detection of oral squamous cell carcinoma by an infrared sensor (feasibility study) (Conference Presentation)
Bibliographic record
Abstract
Oral squamous cell carcinoma (OSCC) is the most prevalent cancer in the oral and maxillofacial region, with a 75% 5-year survival rate dependent on early detection. This study aimed to non-invasively detect OSCC by measuring the thermal difference between carcinogenic tissue and healthy mucosa using an infrared sensor and assess the accuracy of this diagnostic approach. A novel intraoral infrared device was designed to measure intraoral tissue temperature in 20 participants (10 OSCC patients and 10 healthy individuals). Results indicated a significant temperature difference between tumoral and healthy tissues (P<0.001). The device demonstrated high accuracy, with a temperature differential greater than 0.97°C indicating potential OSCC presence (sensitivity=1, specificity=1). Temperatures exceeding 38.42°C suggested malignant lesions (sensitivity=1, specificity=0.9). This feasibility study highlights thermography's potential as a non-invasive diagnostic tool for early OSCC detection. Further research with larger samples is needed to validate these findings and the device's performance.
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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 | 0.001 |
| 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".