Table 10.
Performance metrics obtained with our proposed framework and other classifiers obtained from the literature for CBCD.
| Main Aspects | Reference [17] | Reference [30] | DDFCDSS—This Work | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CV | RS | |||||||||
| Number of Variables | V1:V2 | V1:V3 | V1:4 | V1-V5 | V1:V6 | V1:V9 | V1:V8 | V2,V3,V6,V8,V9 | V1:V9 | |
| Number of Rules or Hidden neurons/technique | SVM | AdaBoostM1 and MAD | 97 | 81 | ||||||
| Performance | Accuracy (%): | - | - | - | - | - | - | 91.37 | 95.9% | 94.0% |
| Sensitivity: | 0.81:0.86 | 0.87:0.92 | 0.82:0.88 | 0.84:0.9 | 0.81:0.86 | 0.75:0.81 | - | 0.937 | 0.901 | |
| Specificity: | 0.7:0.76 | 0.78:0.83 | 0.84:0.9 | 0.81:0.87 | 0.8:0.86 | 0.78:0.84 | - | 0.992 | 1.000 | |
| F-Measure: | - | - | - | - | - | - | 0.914 | 0.964 | 0.948 | |
| Area under curve: | 0.76:0.81 | 0.82:0.86 | 0.87:0.91 | 0.86:0.9 | 0.83:0.88 | 0.81:0.85 | 0.938 | 0.957 | 0.933 | |
| Kappa statistics: | - | - | - | - | - | - | 82.76% | 0.917 | 87.6% | |
| Precision: | - | - | - | - | - | - | 0.919 | 0.994 | 1.000 | |
| Recall: | - | - | - | - | - | - | 0.914 | 0.937 | 0.901 | |
CBCD: Coimbra Breast Cancer Dataset. V: Variable. SVM: Support Vector Machine. MAD: Mean Absolute Deviation. DDFCDSS: Data-driven fuzzy clinical decision support systems, - which are not mentioned in the literature. Bold values indicate the best performance.