Classification of Lung Sounds during Bronchial Provocation Using Waveform Fractal Dimensions
Bibliographic record
Abstract
Lung sounds (LS) of children after bronchoconstriction should differ from baseline LS in terms of amplitude and pattern characteristics. To test these hypotheses, time-domain and fractal based analyses have been applied to LS acquired from eight children ages 9-15 y pre- and post-methacholine challenge (MCh). Change in forced expiratory volume in 1 s after MCh ranged from -4% to -37%, with change proportional to severity of bronchoconstriction. Sounds were recorded over the posterior right lower lung lobe while subjects breathed normally for 60 s with flow measurement, and during 10 s of breath hold (BH). From root-mean-square (RMS) of LS and BH signals, signal-to-noise ratio (SNR) was determined. Two fractal dimension (FD) algorithms were applied, based on signal variance and morphology. Feature vectors for 1-nearest-neighbor classification contained FD and RMS values within flow plateau ranges. Results for LS within 75-600 Hz indicate that the combination of RMS-SNR and morphology-based FD values offers better classification of bronchoconstriction with LS, relative to using RMS-SNR with variance-based FDs and RMS-SNR alone. True positive classification was 90.3%, 63.5% and 58.3% respectively, and false positive classification was 23.4%, 24.9% and 26.1% respectively. Both RMS-SNR and FD values provide useful insight into LS changes post-bronchoconstriction.
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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 | 0.000 | 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".