Table 2.

The classification accuracy of the proposed BNN-based system at different sizes of the dataset.

	Dataset percentage	Sensitivity	Specificity	F1-score	Accuracy
2 Folds	$70\%$	$91.02\%\pm 2.6\%$	$91.07\%\pm 12.6\%$	$89.04\%\pm 2.6\%$	$89.44\%\pm 0.8\%$
	$100\%$	$93.94\%\pm 1.0\%$	$97.30\%\pm 3.8\%$	$95.15\%\pm 1.9\%$	$95.38\%\pm 1.1\%$
4 Folds	$70\%$	$93.54\%\pm 7.5\%$	$93.58\%\pm 7.8\%$	$91.86\%\pm 1.5\%$	$92.22\%\pm 1.3\%$
	$100\%$	$94.62\%\pm 4.4\%$	$98.65\%\pm 2.7\%$	$96.33\%\pm 1.4\%$	$96.54\%\pm 0.8\%$
10 Folds	$70\%$	$93.83\%\pm 8.5\%$	$100\%\pm 0.0\%$	$96.64\%\pm 4.6\%$	$96.11\%\pm 5.3\%$
	$100\%$	$96.75\%\pm 5.5\%$	$96.41\%\pm 4.9\%$	$96.82\%\pm 3.2\%$	$96.54\%\pm 3.8\%$
LOSO	$70\%$	95.45%	95.65%	95.45%	95.56%
	$100\%$	96.15%	99.23%	97.66%	97.69%