… 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 …

… ECG data sources. We also present open research problems, such as the lack of attempts to
address the issue of blood pressure variability in training data … methods applied to ECG 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…

… 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 …

… 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 …

… Diagnostic methods of this … field, machine learning techniques have great potential for
disease diagnosis. We can achieve accurate detection from ECG by using deep learning methods. …

… deep learning applications by constructing a framework to improve the prediction of
cardiac-related diseases using electrocardiogram (ECG) data… signals like electrocardiograms …

… a deep neural network was developed for the automatic classification of primary ECG signals…
In this article, data from the PTB-XL ECG database were used [11]. The PTB-XL database is …