Table 5.

Results from the proposed CNN with hyperparameter optimization.

Classifier	A	R	P	F	K	AUROC	AUPRC
SARS-COV-2 CT-Scan Dataset
Random forest	0.989	0.989	0.989	0.989	0.979	0.950	0.962
MLP	0.993	0.994	0.994	0.993	0.988	0.974	0.970
SVM	0.989	0.990	0.990	0.989	0.980	0.946	0.951
XGBoost	0.990	0.990	0.991	0.990	0.981	0.966	0.962
COVID-CT Dataset
Random forest	0.930	0.932	0.932	0.930	0.860	0.928	0.917
MLP	0.953	0.948	0.948	0.948	0.897	0.932	0.926
SVM	0.930	0.932	0.932	0.927	0.855	0.927	0.915
XGBoost	0.929	0.936	0.929	0.929	0.858	0.930	0.919

Values in bold indicate the best results for all classifiers.