… for ECG data [135] (2018), there have no systematic reviews focusing on deep learning
methods, which we consider to be promising methods for mining ECG data. Therefore, we …

… Machine learning, including deep learning, have shown to be … ECG biomarkers extracted
from machine learning techniques… Deep learning algorithms are designed for learning the data …

… the public databases for ingestion by deep learning models. These efforts have … deep
learning, state-of-the-art prior to its use for ECG analysis, and current applications of deep learning …

… data from cardiology. Compared to these surveys, we only present state-of-the-art deep
learning techniques … , introduction on different deep learning methods, performance evaluation …

… In this study, we have analyzed literature reports that use deep learning on arrhythmia ECG
data. Some important observations obtained as a result of these examinations are as follows…

… This allows deep learning to have large sets of data trained … review of deep learning’s
application in ECG diagnosis has … in studies of deep learning method applied in ECG diagnosis is …

… However, feature selection is a process of removing irrelevant and redundant features (dimensions)
from the data set in the training process of machine learning algorithms. There are …

… In addition to all of these results, in this study, the effect of the number distribution in the
input data on the success of the deep learning model was observed. As far as the arrhythmia …

… three methods for synthesizing artificial ECG signals by using deep learning techniques. To
… This R-wave peaks data set represents a simple form of ECG, as a result, we can use this …

… We found 147 papers using deep-learning methods in EMG signal analysis, ECG signals
analysis, EEG signals analysis, EOG signals analysis, and combinations of signal analysis. …