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Enhanced ECG signal features transformation to RGB matrix imaging for advanced deep learning classification of myocardial infarction and cardiac arrhythmia
Identifying and accurately classifying cardiac abnormalities, including myocardial infarction
(MI) and cardiac arrhythmia (CA), remains a significant challenge in the field of cardiology …
(MI) and cardiac arrhythmia (CA), remains a significant challenge in the field of cardiology …
Pruned lightweight neural networks for arrhythmia classification with clinical 12-Lead ECGs
Real-time electrocardiogram (ECG) monitoring through portable or wearable devices is
critical for detecting lethal arrhythmias. Despite the accuracy of 12-lead ECGs in clinical …
critical for detecting lethal arrhythmias. Despite the accuracy of 12-lead ECGs in clinical …
Multi-criteria Bayesian optimization of Empirical Mode Decomposition and hybrid filters fusion for enhanced ECG signal denoising and classification: Cardiac …
This paper introduces a new advanced model for denoising and classification of ECG
signals, focusing on the use of a hybrid filter and Bayesian optimization. The hybrid filter …
signals, focusing on the use of a hybrid filter and Bayesian optimization. The hybrid filter …
CardioECGNet: A novel deep learning architecture for accurate and automated ECG signal classification across diverse cardiac conditions
Cardiovascular diseases are a leading cause of death worldwide. Hence, early detection of
cardiac arrhythmia is crucial for effective treatment. Electrocardiogram (ECG) signals provide …
cardiac arrhythmia is crucial for effective treatment. Electrocardiogram (ECG) signals provide …
Integrating advanced combined numerical filters for ECG denoising and cardiovascular disease classification using deep learning
In this paper, a novel method for ECG signal processing for cardiovascular disease
classification using deep learning is proposed. The central element of the study is a new …
classification using deep learning is proposed. The central element of the study is a new …
Advancing Cardiac Image Processing: An Innovative Model Utilizing Canny Edge Detection For Enhanced Diagnostics
S Mohamed, MB Elboshy, HA Khater… - 2024 41st National …, 2024 - ieeexplore.ieee.org
Cardiovascular disease is a leading cause of mortality worldwide, necessitating the
development of advanced diagnostic techniques. This research paper introduces an …
development of advanced diagnostic techniques. This research paper introduces an …
Bayesian Methods for Multi-Objective Optimization of Hybrid Numerical Filters in ECG Signal Processing for Accurate Arrhythmia Classification
This study introduces an innovative method for ECG signal processing that combines
advanced filtering techniques, multi-objective Bayesian optimization, and a sophisticated …
advanced filtering techniques, multi-objective Bayesian optimization, and a sophisticated …
A Hybrid CNN-LSTM Model for Accurate Prediction of Cardiac Arrhythmia using ECG Signals
S Varshini, TS Dhanush - 2024 3rd International Conference on …, 2024 - ieeexplore.ieee.org
Cardiac arrhythmia is a significant health concern, necessitating timely and precise
diagnosis to prevent life-threatening complications. This study investigates the potential of …
diagnosis to prevent life-threatening complications. This study investigates the potential of …
High Accuracy Detection of S and T Peaks in ECG Signals
F Aydin, S Usta, M ÖZTÜR, Ö AydoĞDu… - 2024 32nd Signal …, 2024 - ieeexplore.ieee.org
Electrocardiography (ECG) consists of pivotal points named PQRST, and accurately
identifying these points is crucial for diagnosing heart conditions. In detecting ST elevation …
identifying these points is crucial for diagnosing heart conditions. In detecting ST elevation …