Table 4. Evaluation results of four models.
| Indicators | Sensitivity/TPR | Specificity | Accuracy | Precision/PPV | NPV |
|---|---|---|---|---|---|
| Formula | TP/(TP + FN) | TN/(TN + FP) | (TP + TN)/(TP + FN + TN + FP) | TP/(TP + FP) | TN/(TN + FN) |
| 3D VGG | 77.78% | 76.50% | 76.67% | 33.33% | 95.80% |
| 3D ResNet | 69.84% | 85.37% | 83.33% | 41.90% | 94.93% |
| 3D SE-ResNet | 80.95% | 82.49% | 82.29% | 41.13% | 96.63% |
| 3D CA-ResNet | 87.30% | 89.21% | 88.96% | 55.00% | 97.89% |
3D, three-dimensional; VGG, visual geometry group; ResNet, residual network; SE-ResNet, squeeze-and-excitation residual network; CA-ResNet, coordinate attention residual network; TPR, true positive rate; TP, true positive; FP, false positive; TN, true negative; FN, false negative; PPV, positive predictive value; NPV, negative predictive value.