Research Article
An Efficient USE-Net Deep Learning Model for Cancer Detection
Table 6
Performance analysis comparison based on mammogram classification models.
| | Models | Accuracy (%) | Sensitivity (%) | Specificity (%) | Precision (%) | F1-scores (%) |
| | LBP-ANN [17] | 87.65 | 88.58 | 86.59 | NA | 90.86% | | VGG-19-SVM [13] | 95.92 | 92.41 | 95.21 | 91.96% | 92.18% | | TTCNN [18] | 96.57 | 96.11 | 97.03 | NA | NA | | ResNet50-SVM [13] | 96.87 | 94.24 | 96.99 | 95.45% | 94.84% | | Inception-v2ResNet-SVM [13] | 94.76 | 88.86 | 94.72 | 88.14% | 88.49% | | Proposed model | 98.31 | 99.29 | 90.20 | 98.82% | 99.05% |
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