… and store a continuous stream of sensitive health data. Applications of machine learning
techniques for automated analysis of ECG data have been the focus of many recent cardiac …

… and applied to the proposed deep-learning technique. A customized activation … the deep
learning network. The proposed network can extract features automatically from the input data. …

… In this paper, we propose an ensemble of multi-model deep learning methods to
automatically classify heartbeats arrhythmias in highly imbalanced ECG data. Both convolutional …

… on human identification using ECG data. In the recent years, deep learning has shown …
The aim of the study was to combine deep learning techniques with ECG signal for human …

… of interpretability methods to multivariate timeseries and in particular ECG data was
demonstrated in [41], see also [59], [60] for further accounts on interpretability methods for ECG data. …

… selected deep learning methods on a large number of ECG data streams. Specifically, it
investigates the performance of two types of neural networks: the convolutional neural network (…

… a deep learning method to digitize highly noisy ECG scans. Our method extracts the ECG
signal … benefit the development of ECG algorithms and their application to real-world ECG data. …

… Researchers [4–6] investigated many techniques for automatically … machine and deep
learning techniques, typically by using ECG in one or two-dimensional voltage amplitude data …

… In the meantime, to ensure continued support, we are displaying the site without styles and
… Convolutional architectures are well-suited to ECG data due to the repetition of motifs across …

… of ECG-AI training are described in the Supplemental Methods. … predicts time to incident AF
using 12-lead ECG data. … On balance, our findings suggest that deep learning–derived ECG-…