ICBHI
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Respiratory sound classification | ICBHI dataset official (60-40% split) | Specificity85.99 | 42 | |
| Respiratory sound classification | ICBHI 2017 (official) | Specificity85.13 | 32 | |
| 4-class respiratory sound classification | ICBHI 60-40% split official (test) | Specificity85.6 | 31 | |
| 2-class respiratory sound classification | ICBHI 60-40% split official (test) | Specificity81.66 | 16 | |
| Respiratory sound classification | ICBHI | Specificity79.34 | 14 | |
| Respiratory Sound Classification | ICBHI 2017 (test) | Specificity81.66 | 10 | |
| 4-class respiratory sound classification | ICBHI 2017 (official 60-40% split) | Specificity0.8247 | 8 | |
| Respiratory sound 4-class classification | ICBHI 2017 (60/40) | Overall Score56.2 | 8 | |
| Respiratory sound classification | ICBHI dataset | Accuracy94.55 | 7 | |
| 4-class Lung Sound Classification | ICBHI 2017 (test) | Specificity82.05 | 7 | |
| Ternary Chronic Classification | ICBHI 2017 (train-val) | Specificity100 | 7 | |
| Respiratory sound 4-class classification | ICBHI 2017 (80/20 random split) | Specificity84.1 | 6 | |
| Chronic classification (3 classes) | ICBHI challenge dataset 2017 (test) | Accuracy99.519 | 6 | |
| Pathological classification (6 classes) | ICBHI challenge dataset 2017 (test) | Accuracy99.05 | 6 | |
| Respiratory sound 2-class classification | ICBHI 2017 (80/20) | Specificity0.833 | 3 | |
| Pathological Classification | ICBHI 2017 (train val) | Accuracy99 | 3 |
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