Research Article
Diagnosis of Alzheimer’s Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal
Table 2
Comparison of the diagnosis methods used in this paper.
| | Sensitivity | Precision | AUC | Accuracy | | MCI | AD | HC | MCI | AD | HC |
| | KNN | 79.7% | 71.9% | 62.5% | 63.7% | 75.4% | 78.4% | 0.902 | 71.4% | | SVM | 9.4% | 32.8% | 81.3% | 31.6% | 47.7% | 40.3% | 0.593 | 41.1% | | LDA | 28.1% | 53.1% | 50.0% | 45.0% | 43.0% | 48.8% | 0.594 | 43.8% | | Presented CNN | 82.8% | 89.1% | 75.5% | 81.5% | 79.2% | 87.3% | 0.988 | 82.3% |
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