Extended Data Table 4 Comparing the performance of six machine learning models in predicting the LVDD using clinical, ECG-based, and GAN-generated features

From: Synthetic generation of cardiac tissue motion from surface electrocardiograms

  1. We report the sensitivity, specificity, F1 score, accuracy, and AUC with 95% CI in the detection of LV diastolic dysfunction (positive class = presence of LV diastolic dysfunction). AUC = area under the receiver operator characteristic curves, CI = confidence interval, LVDD = LV diastolic dysfunction, DT = decision tree, SVM = support vector machine, KNN = K-nearest neighbor, LR = logistic regression, NB = naïve bayes, RF = random forest.
Back to article page