TABLE 5. Prediction Models Performance.

	A	B	C	D	E	F	G	H*
AUC	0.645	0.639	0.689	0.666	0.656	0.667	0.809	0.969
Accuracy	0.455	0.452	0.602	0.562	0.484	0.506	0.654	0.968
F1	0.321	0.316	0.390	0.363	0.342	0.357	0.511	0.945
Sensitivity	0.362	0.356	0.403	0.384	0.376	0.391	0.556	0.960
Specificity	0.797	0.795	0.809	0.803	0.800	0.803	0.848	0.989
Precision	0.328	0.325	0.404	0.368	0.352	0.357	0.539	0.932

A: regression analysis without PCA; B: regression analysis with PCA; C: random forest without PCA; D: random forest with PCA; E: SVM without PCA; F: SVM with PCA; G: MLP; H*: CNN (proposed framework). PCA: principal component analysis.