Table 6.

The performance of the proposed model related to related work.

Task	Model	AUC	precision	Recall
Ischemic stroke detection	NN Bagging	0.957	0.818	1.000
	LR Bagging	0.957	0.818	1.000
	Hard Vote	0.957	0.818	1.000
	Soft Vote	0.957	0.818	1.000
	stacking_ens_LR	0.966	0.818	1.000
	DA(Lasso + PCA + Lasso)[45]	0.925
NIHSS prediction	NN Bagging	0.995	0.875	0.875
	LR Bagging	1.000	1.000	0.875
	Hard Vote	0.917	0.875	0.875
	Soft Vote	0.917	0.875	0.875
	stacking_ens_LR	0.990	0.875	0.875
	DA(Lasso + PCA + Lasso)[45]	0.853
Outcome Prediction	NB Bagging	0.976	0.800	0.889
	KNN Bagging	0.894	0.600	1.000
	Soft Vote	0.879	0.727	0.889
	stacking_ens_LR	0.903	0.583	0.778
	LR (Lasso combined)[53]	0.971
	LR (lasso WB)[53]	0.936
	CTI + survF [48]	0.949
	NB(Lasso + PCA + Lasso)[45]	0.828
	NN(IWS)[52]	0.904