Oct 19, 2023 · Therefore, an automated system that can assist physicians in the easy detection of arrhythmia is needed. The main objective of this study was to create an automated deep learning model capable of accurately classifying ECG signals into three categories: cardiac arrhythmia (ARR), congestive heart failure (CHF), and normal sinus rhythm (NSR).

Jan 1, 2017 · In this study, a deep learning framework previously trained on a general image data set is transferred to carry out automatic ECG arrhythmia diagnostics by classifying patient ECG’s into corresponding cardiac conditions.

Deep Learning (DL) architectures have been successfully employed for arrhythmia detection and classification and offered superior performance to traditional shallow Machine Learning (ML) approaches. This survey categorizes and compares the DL architectures used in ECG arrhythmia detection from 2017–2023 that have exhibited superior performance.

Several studies suggest multiple approaches for identifying cardiac issues using machine learning [23, 24, 25, 26]. The ML approach consists of several processes, including image preprocessing, feature extraction, training and parameter tuning, evaluating the model, and subsequently making predictions using the model.

Nov 1, 2019 · In this work, we reviewed the recent advancement of deep learning methods for automatic arrhythmia detection. We summarized existing literature from five aspects: utilized dataset, application, type of input data, model architecture, and performance evaluation. We also reported limitations of reviewed papers and potential future opportunities.

Nov 1, 2022 · Deep learning model such as deep belief networks is used with cuckoo search bio-inspired algorithm for finding the accurate prediction of cardiac disease.

Apr 7, 2025 · A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly improve survival outcomes. The electrocardiogram (ECG) remains the standard method for detecting arrhythmias, traditionally analyzed by cardiolo ...

Sep 27, 2023 · In this study, we employed a deep learning approach utilizing a convolutional neural network (CNN) to automate the detection of cardiovascular diseases using ECG images. The proposed model...

Mar 15, 2025 · Given the significant risk that heart disease, particularly heart attacks, poses to individuals’ lives, it is crucial to develop effective techniques for early detection. Advanced machine learning and deep learning algorithms have the ability to predict heart attacks by analyzing a patient’s medical history and overall health. These algorithms can process large datasets, extracting ...

In the pre-processing node, the noise-reduced and less interfering full-frame HS signal is normalized and segmented. Function extraction and classification is performed by the signal...