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Table 3 ROC curve analysis of machine learning algorithms for detecting CAD

From: Machine learning-enhanced echocardiography for screening coronary artery disease

Model

Sensitivity

Specificity

ROC AUC

Gradient boosting

0.952

0.691

0.852

Catboost

0.942

0.682

0.829

Random forest

0.942

0.638

0.817

Extra trees

0.914

0.628

0.804

Light gradient boosting

0.932

0.664

0.824

Xgboost

0.932

0.664

0.824

  1. AUC Area under the curve, ROC Receiver operator characteristics