Author Correction: Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features

Correction to: Scientific Reports 10.1038/s41598-020-63566-8, published online 21 April 2020

This Article contains an error in the order of the Figures. Figures 1 and 2 were published as Figures 2 and 1 respectively. The Correct Figures 1 and 2 appear below. The Figure legends are correct.

Figure 1.

(A) CNN architecture with an input layer, four hidden layers, and a flatten input that will be fed to dense layers. (1D: one dimension) (B) The architecture of our ANN.

Figure 2.

(A) Means and standard deviations of the prediction accuracies of each algorithm. Single asterisks (*) indicates a statistically significant difference between the prediction accuracies of different algorithms (CNN > ANN, SVM, and KNN, p < 0.001). (B) ROC AUCs (receiver operating characteristic area under curves) of CNN, ANN, SVM, and KNN to predict VTA 60 seconds before the occurrence. TPR: True Positive Rate and FPR: False Positive Rate accuracies.