ECG
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Synthetic Time Series Generation | ECG | Average ELBO1.68 | 48 | |
| Multivariate Time-series Forecasting | ECG (test) | MAE0.04 | 33 | |
| Classification | ECG | Accuracy99.84 | 30 | |
| Synthetic time series generation | ECG | FID Score0.08 | 24 | |
| Univariate Time Series Anomaly Detection | ECG UCR Archive (test) | F1 Score91.8 | 22 | |
| Classification | ECG (5% labels) | Accuracy84.95 | 19 | |
| Classification | ECG (1% labels) | Accuracy85.74 | 19 | |
| Knowledge-based reasoning | ECG | Accuracy (%)30.3 | 19 | |
| Time Series Classification | ECG | Accuracy95.33 | 15 | |
| Multivariate Time Series Forecasting | ECG | MAE0.052 | 14 | |
| Short-term forecasting | ECG | MAE0.053 | 14 | |
| Time Series Classification | ECG (test) | Accuracy88 | 14 | |
| Multivariate Time Series Classification | ECG (test) | Accuracy89.2 | 13 | |
| Multivariate Time Series Classification | ECG | Accuracy93 | 13 | |
| Sex Classification | ECG (test) | F1 Score0.69 | 12 | |
| Age Estimation | ECG (test) | MAE12.83 | 12 | |
| RR Interval Estimation | ECG (test) | MAE (ms)76.37 | 12 | |
| Time Series Anomaly Detection | ECG | AUC-PR80.9 | 12 | |
| ECG Classification | ECG | 1-F1 Score0.28 | 9 | |
| Classification | ECG | Accuracy87.41 | 8 | |
| Time Series Generation | ECG5k (70% drop) | DS0.4 | 8 | |
| Time Series Generation | ECG200 (30% drop) | DS0.188 | 8 | |
| Risk Evaluation | ECG Abnormal | Accuracy99.737 | 7 | |
| Forecasting | ECG SciML (test) | MSE0.851 | 7 | |
| Forecasting | ECG | KL Divergence0.065 | 7 |
Showing 25 of 50 rows