Figure 2.

Feature reduction of the hybrid model

(A) The AUC and AP values of the XGBoost model with various numbers of features. According to the contribution of each feature to the VCI diagnosis in descending order, sequential forward selection was performed from 33 pre-selected features.

(B) Accuracy, sensitivity, specificity, F1-score, AUC, and AP of the hybrid model with 8 features and 33 features. AUC, area under the receiver operating characteristic curve; AP, area under the precision-recall curve; ACC, accuracy; SEN, sensitivity; SPE, specificity; XGBoost, extreme gradient boosting; VCI, vascular cognitive impairment.