Table 6.
Performance of the component of phonetic motor planning in identifying patients with ADRD
| Algorithms | Precision | Recall | F1-score | AUC-ROC | Accuracy |
|---|---|---|---|---|---|
| XGBoost | 79.41 | 77.14 | 78.26 | 80.32 | 78.87 |
| Random Forest | 78.47 | 77.84 | 78.13 | 83.07 | 78.53 |
| ExtraTrees | 76.58 | 77.77 | 77.15 | 83.34 | 77.29 |
| AdaBoost | 73.73 | 74.285 | 74.01 | 77.22 | 74.27 |
| SVM | 70.27 | 74.28 | 72.22 | 82.31 | 71.83 |
| Logistic Regression | 68.42 | 74.28 | 71.23 | 75.55 | 70.42 |