Table 3.
Results of FFNN according to the combined features of the GoogLeNet and DenseNet-12 models.
| Models | Classes of AD | Accuracy % | Sensitivity % | AUC % | Precision % | Specificity % |
|---|---|---|---|---|---|---|
| FFNN based on the merging of CNN features before PCA | Mild_Demented | 94.4 | 94.27 | 97.52 | 93.9 | 98.96 |
| Moderate_Demented | 69.2 | 69.44 | 84.56 | 69.2 | 99.62 | |
| Non_Demented | 98.6 | 98.84 | 98.25 | 98.9 | 99.1 | |
| Very_Mild_Demented | 97.1 | 97.24 | 96.67 | 96.75 | 98.37 | |
| average ratio | 97.20 | 89.95 | 94.25 | 89.69 | 99.01 | |
| FFNN based on the merging of CNN features after PCA | Mild_Demented | 96.1 | 96.29 | 97.95 | 96.1 | 99.4 |
| Moderate_Demented | 92.3 | 92.1 | 94.64 | 92.3 | 99.82 | |
| Non_Demented | 99.2 | 98.78 | 98.1 | 99.8 | 99.71 | |
| Very_Mild_Demented | 99.3 | 99.24 | 97.54 | 98.5 | 99.22 | |
| average ratio | 98.80 | 96.60 | 97.06 | 96.68 | 99.54 |