Publisher Correction: Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.

In the version of this article originally published, the x axis labels in Fig. 1a were incorrect. The labels originally were 'Specificity,' but should have been '1 - Specificity.

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.

Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning present an opportunity to substantially improve the accuracy and scalability of automated ECG analysis. However, a comprehensive evaluation of an end-to-end deep learning approach for ECG analysis across a wide variety of diagnostic classes has not been previously reported.