Table 9 Performance evaluation in comparison to related work on Mini-DDSM dataset.
Reference | Year | Accuracy (%) | Sensitivity (%) | Specificity (%) | Precision (%) | F1 Score |
|---|---|---|---|---|---|---|
2019 | 82.02 | – | – | – | – | |
2019 | 94.55 | 95.60 | 95.36 | – | – | |
2020 | 85.71 | 87.30 | 84.00 | 85.70 | – | |
2020 | 88.00 | 91.00 | – | 85.00 | ||
2020 | 90.91 | 82.96 | 97.38 | – | – | |
2021 | 88.00 | – | – | – | – | |
2021 | 88.70 | 84.10 | 93.00 | 91.70 | – | |
2022 | 90.68 | 92.72 | 88.21 | - | – | |
2023 | 92.00 | 92.00 | 92.00 | 93.00 | 0.93 | |
2023 | 82.35 | – | – | – | – | |
Proposed - XGBoost | 2024 | 95.00 | 95.00 | 95.00 | 95.00 | 0.97 |
Proposed - AdaBoost | 2024 | 86.67 | 86.66 | 93.33 | 87.66 | 0.86 |
Proposed - CatBoost | 2024 | 93.33 | 93.33 | 96.33 | 93.33 | 0.93 |
