… methods proposed by them are analyzed. We also presented several applications on a
heartbeat … purpose of evaluating commonly used deep learning techniques. This paper provided …

… Deep learning methods have shown promise in healthcare prediction challenges involving
ECG data. This paper aims to apply deep learning techniques on the publicly available …

… In our future work, we aim to evaluate the performance of GRUs for abnormal heartbeat
detection on mobile devices. Moreover, we will also keep searching for larger heartbeat datasets …

… data mining and machine learning techniques. Therefore, a deep learning technique is …
Recently, deep learning techniques have been used by many companies, including Adobe, …

… precise classification of heartbeats along with the accurate detection of … an ensemble of
deep neural networks that involves the … superior results in heartbeat detection and classification …

… In this section, we present the methodology used to train CNN for ECG heartbeat recognition.
Our method aims to validate the response of a well-known QRS complex detector from the …

… technique is introduced in this work to meet the challenges faced by classify the ECG beats.
Recently, deep learning techniques … Complexity of heartbeat types in training and testing (…

… technique in study of heart beat irregularities such as cardiac arrhythmias, sinus rhythms and
heart failure. It is a significant and popular technique to classify and detect … in detection of …

… We test the new learning method on a … detection result compared with a state-of-the-art
method. We demonstrate how the advanced machine learning technology can learn and detect …

… techniques to analyze the huge amounts of data generated. We show that our heartbeat
classification method … more complicated feature selection techniques and complex calculations. …