Sleep Staging on ISRUC (test)
82.4AccuracyCNN
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| CNN2019.10 | 82.4 | 87.8 | 0.772 | — | |
| SLEEPER-GBTPrototypes=96, Classifier=Gradient Boosting Trees2019.10 | 80.1 | 86 | 0.741 | — | |
| CBraMod-MTDPPretrain Dataset (Hours)=2250, Pretraining dataset size=25%, Fine-tuning=true2026.03 | 79.41 | 80.87 | — | 75.54 | |
| CBraMod-MTDPPretrain Dataset (Hours)=9000, Pretraining dataset size=100%, Fine-tuning=true2026.03 | 79.38 | 80.49 | — | 75.12 | |
| CBraModPretrain Dataset (Hours)=9000, Pretraining dataset size=100%, Fine-tuning=true2026.03 | 78.65 | 80.11 | — | 74.42 | |
| SLEEPER-DTPrototypes=96, Classifier=Decision Tree2019.10 | 78.5 | 84.7 | 0.72 | — | |
| CBraModPretrain Dataset (Hours)=2250, Pretraining dataset size=25%, Fine-tuning=true2026.03 | 77.19 | 79.58 | — | 73.97 | |
| SLEEPER-LRPrototypes=96, Classifier=Logistic Regression2019.10 | 77 | 84.9 | 0.699 | — | |
| LaBraMPretrain Dataset (Hours)=2500, Fine-tuning=true2026.03 | 76.33 | 78.1 | — | 72.31 | |
| BIOTPretrain Dataset (Hours)=122, Fine-tuning=true2026.03 | 75.27 | 77.9 | — | 71.92 | |
| Rule & GBTRules=96, Classifier=Gradient Boosting Trees2019.10 | 69.3 | 78.8 | 0.594 | — | |
| Rule & LRRules=96, Classifier=Logistic Regression2019.10 | 69.1 | 79 | 0.593 | — | |
| Rule & DTRules=96, Classifier=Decision Tree2019.10 | 67.1 | 78.2 | 0.564 | — | |
| Mimic learning - GBTClassifier=Gradient Boosting Trees2019.10 | 62.1 | 76.4 | 0.514 | — |