Table 2.

Performance of the Radiomics, Clinical and Clinical-Radiomics Models

Datasets	Models	AUC (95% CI)	ACC	SEN	SPE	PPV	NPV
Training cohort	R-model	0.775(0.719, 0.830)	0.713	0.796	0.617	0.705	0.725
	C-model	0.802(0.749, 0.854)	0.742	0.707	0.781	0.788	0.699
	CR-model	0.880(0.840, 0.920)	0.807	0.776	0.844	0.851	0.766
Internal validation	R-model	0.752(0.662, 0.842)	0.723	0.656	0.8	0.792	0.667
Cohort	C-model	0.736(0.644, 0.828)	0.731	0.812	0.636	0.722	0.745
	CR-model	0.807(0.728, 0.887)	0.748	0.688	0.818	0.815	0.692
External validation	R-model	0.747(0.658, 0.836)	0.713	0.764	0.64	0.753	0.653
Cohort	C-model	0.789(0.709, 0.870)	0.77	0.972	0.48	0.729	0.923
	CR-model	0.815(0.740, 0.891)	0.779	0.931	0.56	0.753	0.848

Abbreviations: R-model, radiomics model; C-model, clinical model; CR-model, clinical-radiomics model; AUC, area under the receiver operating curve; ACC, accuracy; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; SEN, sensitivity; SPE, specificity.