Fig. 3
From: Machine learning-enhanced echocardiography for screening coronary artery disease
Changes in the curve of ROC AUC with different feature combinations, including the ten best classifiers for each feature combination. Different feature panels screened by MDA (27 features), r coefficient (33 features), collinearity diagnostics (14 features), and the importance across all the tested classifiers (39 features). Stepwise combinations of 5 (overlapped features: GWI, G peak SL Full (Avg), Systolic BP., Diastolic BP, LASr R-Wave (Avg)), 30, 44, 59, 69, 79, 106, and 235 features were tested by classifiers