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A novel approach for coronary artery disease diagnosis using hybrid particle swarm optimization based emotional neural network
Coronary artery disease (CAD) can cause serious conditions such as severe heart attack,
heart failure, and angina in patients with cardiovascular problems. These conditions may be …
heart failure, and angina in patients with cardiovascular problems. These conditions may be …
A study on ECG signal characterization and practical implementation of some ECG characterization techniques
The role of ECG is pivotal in medical field for the analysis of cardiac physiology and
abnormalities. The interpretation of ECG signal is performed by signal processing algorithms …
abnormalities. The interpretation of ECG signal is performed by signal processing algorithms …
Detection of ventricular arrhythmia using hybrid time–frequency-based features and deep neural network
Sudden cardiac death (SCD) is a major cause of death among patients with heart diseases.
It occurs mainly due to ventricular tachyarrhythmia (VTA) which includes ventricular …
It occurs mainly due to ventricular tachyarrhythmia (VTA) which includes ventricular …
A machine-learning approach for detection and quantification of QRS fragmentation
Objective: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial
scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is …
scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is …
Heart rate variability features from nonlinear cardiac dynamics in identification of diabetes using artificial neural network and support vector machine
Diabetes mellitus (DM) is a multifactorial disease characterized by hyperglycemia. The type
1 and type 2 DM are two different conditions with insulin deficiency and insulin resistance …
1 and type 2 DM are two different conditions with insulin deficiency and insulin resistance …
[HTML][HTML] A nonlinear analysis of cardiovascular diseases using multi-scale analysis and generalized hurst exponent
S Lahmiri - Healthcare Analytics, 2023 - Elsevier
Congestive heart failure (CHF) and arrhythmia (ARR) are common heart diseases that affect
a growing population of patients worldwide. In this work, we employ multi-scale analysis …
a growing population of patients worldwide. In this work, we employ multi-scale analysis …
Automated detection of heart defects in athletes based on electrocardiography and artificial neural network
Electrocardiography (ECG) has proven to be one of the most efficient ways of tracking heart
defects in athletes. However, the interpretation of electrocardiograms often require the …
defects in athletes. However, the interpretation of electrocardiograms often require the …
The Hybrid Method of VMD‐PSR‐SVD and Improved Binary PSO‐KNN for Fault Diagnosis of Bearing
S Fei - Shock and Vibration, 2019 - Wiley Online Library
Fault diagnosis of bearing based on variational mode decomposition (VMD)‐phase space
reconstruction (PSR)‐singular value decomposition (SVD) and improved binary particle …
reconstruction (PSR)‐singular value decomposition (SVD) and improved binary particle …
[HTML][HTML] Automated detection of caffeinated coffee-induced short-term effects on ECG signals using EMD, DWT, and WPD
The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched.
In the current study, the occurrence of coffee-induced short-term changes in …
In the current study, the occurrence of coffee-induced short-term changes in …
Decision Support System for Predicting Ventricular Arrhythmias Using Non-linear Features of ECG Signals
Automated methods using computer-aided decision-making process are effectively used for
timely detection of VAs which are the most life-threatening conditions. In this work, we have …
timely detection of VAs which are the most life-threatening conditions. In this work, we have …