Table 2.
FFNN results with features of GoogLeNet and DenseNet-121.
| Models | Classes of AD | Accuracy % | Sensitivity % | AUC % | Precision % | Specificity % |
|---|---|---|---|---|---|---|
| FFNN basec on features from GoogLeNet | Mild_Demented | 88.8 | 89.12 | 92.51 | 85.5 | 97.68 |
| Moderate_Demented | 69.2 | 69.36 | 85.72 | 90 | 99.73 | |
| Non_Demented | 97.7 | 98.29 | 97.25 | 96.9 | 97.18 | |
| Very_Mild_Demented | 94 | 93.87 | 94.69 | 95.9 | 98.41 | |
| average ratio | 94.80 | 87.66 | 92.54 | 92.08 | 98.25 | |
| FFNN basec on features from DenseNet-121 | Mild_Demented | 83.2 | 83.34 | 91.49 | 85.6 | 98.44 |
| Moderate_Demented | 69.2 | 69.1 | 89.12 | 81.8 | 99.55 | |
| Non_Demented | 97 | 97.21 | 96.84 | 94.8 | 95.16 | |
| Very_Mild_Demented | 93.5 | 93.97 | 95.79 | 95.2 | 97.38 | |
| average ratio | 93.60 | 85.91 | 93.31 | 89.35 | 97.63 |