Table 3.

${\text{NN}}_{RS\&LP}$, ${\text{NN}}_{\mathit{SM}}$ and LRs characteristics for the HFDB and the IDB

	Architecture		HFDB	IDB
			[16 13 12]	[11 9 1]
${\text{NN}}_{RS\&LP}$	Learning	AUC (%)	99	98
	Testing	AUC (%)	84	83
		CI (%)	[73–95]	[75–91]
		ACC (%)	75	76
${\text{NN}}_{\mathit{SM}}$	Learning	AUC (%)	86	77
	Testing	AUC (%)	83	73
		CI (%)	[72–94]	[60–87]
		ACC (%)	75	67
LR	Learning	AUC (%)	89	88
	Testing	AUC (%)	61	77
		CI (%)	[46–75]	[68–86]
		ACC (%)	54	71