Table 1:

Classification performance on the Physionet Challenge 2012 data set. We report mean and standard deviation (across 10 folds) for each metric. We use the following abbreviations: R: raw time series, H: hand-designed features, NNet(I,L): L-layer neural network with input I

	AUROC	AUPRC	Precision@90%Recall
Raw Time Series (R)	0.786848 ± 0.028957	0.407419 ± 0.042878	0.221303 ± 0.017106
Hand-designed Features (H)	0.828652 ± 0.021065	0.467742 ± 0.047852	0.259324 ± 0.049400
NNet(R,3)	0.820760 ± 0.021021	0.444315 ± 0.032367	0.255792 ± 0.030306
H+R	0.822907 ± 0.018251	0.438160 ± 0.035444	0.255608 ± 0.031871
H+NNet(R,3)	0.845015 ± 0.016525	0.486791 ± 0.047373	0.291411 ± 0.033500