Fluoroscence bronhoscopy
Bibliographic record
Abstract
BACKGROUND: Fluorescence bronchoscopy is one of the methods of the early detection of lung cancer that involves the large airways. The method is based on the detection of the altered autofluorescence of malignantly transformed tissue, and confirmed by biopsy and histopathologic examination. METHOD: Fluorescence bronchoscopy was performed in 18 patients, mean age of 51.2 years (male n = 12, female n = 6) due to the suspected lung cancer. Fluorescence bronchoscopy was performed using the Xillix LIFE-Lung System, Vancouver, Canada. After conventional white-light bronchoscopy, the tracheobronchial tree was illuminated by blue light (442 nm) using helium-cadmium laser, and the results of autofluorescence were classified into three classes. Normal mucosa was of green fluorescence (Class I), abnormal mucosa was red or dark brown fluorescence (Class II and II), which was the indication for performing biopsy. RESULTS: Normal endoscopy findings were established in 15 patients by conventional bronchoscopy. In the same group, by fluorescence bronchoscopy, Class I of fluorescence (normal finding) was found in 9 patients, while Class II changes occurred in 6 patients. Histopathologic analysis of bronchial mucosa with Class II changes was performed detecting planocellular carcinoma in situ in one patient. Tumor-like changes were detected in 3 patients by conventional bronchoscopy, and were determined as Class III changes by fluorescence bronchoscopy. By the biopsy of these chages carcinoma was documented in 2 patients while in one patient metaplasia of epithelium and granulation tissue around aspirated foreign body was detected. CONCLUSION: Fluorescence bronchoscopy is one of the methods for detecting metaplasia, carcinoma in situ and cancerous changes of bronchial epithelium in the large airways. However, the high rate of falsely positive findings represents a limitation of this method.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.031 | 0.008 |
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".