Table 3 Predictive performance of subjective findings, radiomics signature and radiomics nomogram models for differentiating lung adenocarcinomas and granulomatous lesions in patients with SCSNs
|  | Training set (n = 150) | External validation set (n = 64) | ||||
|---|---|---|---|---|---|---|
Subjective findings model | Radiomics signature | Radiomics nomogram | Subjective findings model | Radiomics signature | Radiomics nomogram | |
AUC (95% CI) | 0.762 (0.686–0.828) | 0.834 (0.764–0.889) | 0.885 (0.823–0.931) | 0.619 (0.489–0.738) | 0.798 (0.679–0.888) | 0.808 (0.690–0.896) |
Sensitivity | 0.831 (64/77) | 0.766 (59/77) | 0.727 (56/77) | 0.657 (23/35) | 0.714 (25/35) | 0.714 (25/35) |
Specificity | 0.603 (44/73) | 0.781 (57/73) | 0.904 (66/73) | 0.621 (18/29) | 0.828 (24/29) | 0.828 (24/29) |
Accuracy | 0.720 (108/150) | 0.773 (116/150) | 0.813 (122/150) | 0.641 (41/64) | 0.766 (49/64) | 0.766 (49/64) |
PPV | 0.688 (64/93) | 0.787 (59/75) | 0.889 (56/63) | 0.676 (23/34) | 0.833 (25/30) | 0.833 (25/30) |
NPV | 0.772Â (44/57) | 0.760 (57/75) | 0.759 (66/87) | 0.600 (18/30) | 0.706 (24/34) | 0.706 (24/34) |