Table 1.

Seizure identification performance metrics of our method (VAE) vs. t-SNE followed by K-means and hierarchical clustering. We report all prediction performance metrics as averaged over the 5 test folds, along with the corresponding standard deviations. Lower p-values indicate higher significance in identification performance.

Dataset	Method	Precision	Recall	Accuracy	AUC	p-Value ↓
UPenn	VAE	0.76 ± 0.05	0.78 ± 0.05	0.79 ± 0.04	0.83 ± 0.06	1e−106
	K-means	0.33 ± 0.0	0.5 ± 0.0	0.5 ± 0.0	0.56 ± 0.0	1.0
	Hierarchical	0.33 ± 0.0	0.5 ± 0.0	0.67 ± 0.0	0.5 ± 0.0	1.0
TUH	VAE	0.67 ± 0.08	0.69 ± 0.08	0.75 ± 0.08	0.67 ± 0.13	1e−102
	K-means	0.17 ± 0.0	0.5 ± 0.0	0.35 ± 0.0	0.57 ± 0.0	1.0
	Hierarchical	0.17 ± 0.0	0.5 ± 0.0	0.35 ± 0.0	0.45 ± 0.0	1.0
MIT	VAE	0.54 ± 0.02	0.64 ± 0.05	0.68 ± 0.09	0.68 ± 0.06	1e−21
	K-means	0.33 ± 0.0	0.5 ± 0.0	0.5 ± 0.0	0.59 ± 0.0	1.0
	Hierarchical	0.33 ± 0.0	0.5 ± 0.0	0.67 ± 0.0	0.53 ± 0.0	1.0