Table 3.

Recognition ability of all models for patients with CAD

Model	Training set						Test set
	AUC (95%CI)	SEN	SPE	ACC	PPV	NPV	AUC (95%CI)	SEN	SPE	ACC	PPV	NPV
Model 1	0.811(0.741–0.881)	0.784	0.772	0.780	0.667	0.860	0.691(0.564–0.817)	0.577	0.659	0.629	0.500	0.725
Model 2	0.960(0.934–0.987)	0.951	0.877	0.925	0.909	0.933	0.930(0.871–0.989)	0.885	0.773	0.814	0.697	0.919
Model 3	0.812(0.742–0.882)	0.784	0.772	0.780	0.667	0.860	0.693(0.567–0.819)	0.577	0.659	0.629	0.500	0.725
Model 4	0.961(0.934–0.988)	0.951	0.877	0.925	0.909	0.933	0.929(0.869–0.989)	0.885	0.773	0.814	0.697	0.919

AUC area under curve, 95%CI 95% confidence interval, SEN sensitivity, SPE specificity, ACC accuracy, PPV positive predictive value, NPV negative predictive value

Model 1 clinical factors model

Model 2 clinical factors and imaging indexes model

Model 3 clinical factors and Radscore model

Model 4 combined model