[Retracted] Smart Heart Disease Prediction System with IoT and Fog Computing Sectors Enabled by Cascaded Deep Learning Model

Table 5

Comparative analysis of the smart healthcare model with metaheuristic-based algorithms by taking the k-fold validation as 5.

Measures	PSO-CCNN [28]	GWO-CCNN [29]	WOA-CCNN [30]	DHOA-CCNN [31]	GSO-CCNN
“Accuracy”	0.9508	0.9433	0.9483	0.9405	0.9721
“Sensitivity”	0.951	0.94	0.9482	0.9314	0.97667
“Specificity”	0.9506	0.9466	0.9484	0.9496	0.96525
“Precision”	0.95062	0.94625	0.94839	0.94867	0.97683
“FPR”	0.0494	0.0534	0.0516	0.0504	0.03475
“FNR”	0.049	0.06	0.0518	0.0686	0.023333
“NPV”	0.9506	0.9466	0.9484	0.9496	0.96525
“FDR”	0.04938	0.053755	0.05161	0.051334	0.023171
“F1-score”	0.95081	0.94311	0.94829	0.93995	0.97675
“MCC”	0.9016	0.88662	0.8966	0.88115	0.94188