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. 2022 Dec 27;128(1):68–80. doi: 10.1007/s11547-022-01580-8

Table 2.

The performance of the 3D-CNN optimal model in internal test set and external test set

Parameters Internal test set External test set
3D-CNN optimal model Radiologist1 Radiologist2 3D-CNN optimal model Radiologist1 Radiologist2
Accuracy 0.989 0.805 0.828 0.934 0.803 0.803
AUC (95%CI)

0.988

(0.962–1.000)

0.804

(0.708–0.901)

0.827

(0.735–0.920)

0.933

(0.860–1.000)

0.804

(0.682–0.894)

0.803

(0.686–0.919)

Corrected AUC 0.989 0.806 0.829 0.932 0.802 0.800
Sensitivity/recall 1.000 0.818 0.841 1.000 0.774 0.839
Specificity 0.977 0.791 0.814 0.867 0.833 0.767
PPV/precision 0.978 0.800 0.822 0.886 0.828 0.788
NPV 1.000 0.810 0.833 1.000 0.781 0.821
F1-score 0.989 0.809 0.831 0.939 0.800 0.813

AUC Area-sunder-the-curve, PPV Positive predictive value, NPV Negative predictive value