Table 2 Predict performances of four models on the testing set.

From: Prediction of ischemic stroke in patients with H-type hypertension based on biomarker

 

AUC (95%CI)

Sensitivity

Specificity

Accuracy

PPV

NPV

Logistic model

0.905 (0.887–0.924)#

0.745

0.905

0.833

0.860

0.816

SVM model

0.896 (0.876–0.915)*

0.778

0.851

0.819

0.806

0.828

Random forest model

0.893 (0.872–0.914)

0.820

0.840

0.831

0.803

0.854

XGBoost model

0.909 (0.890–0.927)

0.825

0.860

0.845

0.825

0.860

  1. #There was no significant difference in AUC between the logistic model and the XGBoost model by Delong test; *There was no significant difference in AUC between the SVM model and the random forest model by Delong test; AUC: area under curve; CI: confidence interval; PPV: positive predictive value; NPV: negative predictive value; SVM: support vector machine.
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