Automated atrial fibrillation detection using a hybrid CNN-LSTM network on imbalanced ECG datasets
Atrial fibrillation is a heart arrhythmia strongly associated with other heart-related
complications that can increase the risk of strokes and heart failure. Manual …
complications that can increase the risk of strokes and heart failure. Manual …
[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
[HTML][HTML] Digital biomarkers and algorithms for detection of atrial fibrillation using surface electrocardiograms: A systematic review
Aims Automated detection of atrial fibrillation (AF) in continuous rhythm registrations is
essential in order to prevent complications and optimize treatment of AF. Many algorithms …
essential in order to prevent complications and optimize treatment of AF. Many algorithms …
[HTML][HTML] Phonocardiogram signal processing for automatic diagnosis of congenital heart disorders through fusion of temporal and cepstral features
Congenital heart disease (CHD) is a heart disorder associated with the devastating
indications that result in increased mortality, increased morbidity, increased healthcare …
indications that result in increased mortality, increased morbidity, increased healthcare …
Multilevel classification and detection of cardiac arrhythmias with high-resolution superlet transform and deep convolution neural network
Atrial fibrillation and ventricular fibrillation are the two most common cardiac arrhythmia.
These cardiac arrhythmias cause heart strokes and other heart complications leading to an …
These cardiac arrhythmias cause heart strokes and other heart complications leading to an …
An automated detection of atrial fibrillation from single‑lead ECG using HRV features and machine learning
AS Udawat, P Singh - Journal of Electrocardiology, 2022 - Elsevier
Background Atrial fibrillation (AF) is a disorder of the heart rhythm where irregular and rapid
heartbeats are observed. This supraventricular arrhythmia may increase the risk of blood …
heartbeats are observed. This supraventricular arrhythmia may increase the risk of blood …
MGNN: A multiscale grouped convolutional neural network for efficient atrial fibrillation detection
S Liu, A Wang, X Deng, C Yang - Computers in Biology and Medicine, 2022 - Elsevier
The reliable detection of atrial fibrillation (AF) is of great significance for monitoring disease
progression and developing tailored care paths. In this work, we proposed a novel and …
progression and developing tailored care paths. In this work, we proposed a novel and …
[HTML][HTML] A deep learning approach for atrial fibrillation classification using multi-feature time series data from ecg and ppg
Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to
patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and …
patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and …
Evaluation of fuzzy membership functions for linguistic rule-based classifier focused on explainability, interpretability and reliability
S Porebski - Expert Systems with Applications, 2022 - Elsevier
Objective: Decision support systems focus on their interpretability with a different caution.
The majority of approaches utilize reliable optimization techniques to achieve high …
The majority of approaches utilize reliable optimization techniques to achieve high …
Atrial fibrillation detection using heart rate variability and atrial activity: A hybrid approach
G Hirsch, SH Jensen, ES Poulsen… - Expert Systems with …, 2021 - Elsevier
Goal: Develop a real-time hybrid scheme for the automatic detection of atrial fibrillation (AF),
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …