Table 3 Comparative performance metrics and statistical significance.
From: An automatic classification of breast cancer using fuzzy scoring based ResNet CNN model
Model | ROC-AUC | Precision | Recall | F1-Score | Accuracy% | t-test p-value | Wilcoxon P-VALUE |
|---|---|---|---|---|---|---|---|
FS-ResNet CNN (Proposed) | 0.981 ± 0.005 | 0.962 ± 0.006 | 0.950 ± 0.007 | 0.956 ± 0.004 | 96.8 ± 0.9 | - | - |
DCE-MRI + Classifier | 0.912 ± 0.009 | 0.881 ± 0.011 | 0.869 ± 0.010 | 0.875 ± 0.012 | 89.6 ± 1.2 | 0.0012 | 0.0018 |
CNN(Vanilla) | 0.931 ± 0.006 | 0.902 ± 0.007 | 0.888 ± 0.009 | 0.895 ± 0.008 | 91.1 ± 1.0 | 0.0021 | 0.0025 |
