A review of arrhythmia detection based on electrocardiogram with artificial intelligence
Introduction With the widespread availability of portable electrocardiogram (ECG) devices,
there will be a surge in ECG diagnoses. Traditional computer-aided diagnosis of arrhythmia …
there will be a surge in ECG diagnoses. Traditional computer-aided diagnosis of arrhythmia …
A novel interpretable method based on dual-level attentional deep neural network for actual multilabel arrhythmia detection
Arrhythmia accounts for more than 80% of sudden cardiac death, and its incidence rate has
increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) …
increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) …
A novel P-QRS-T wave localization method in ECG signals based on hybrid neural networks
As the number of people suffering from cardiovascular diseases increases every year, it
becomes essential to have an accurate automatic electrocardiogram (ECG) diagnosis …
becomes essential to have an accurate automatic electrocardiogram (ECG) diagnosis …
A deep learning-based acute coronary syndrome-related disease classification method: A cohort study for network interpretability and transfer learning
Accurate and efficient diagnosis of acute coronary syndrome (ACS)-related cardiac diseases
is crucial for optimizing medical resources and enhancing clinical treatment efficiency. In this …
is crucial for optimizing medical resources and enhancing clinical treatment efficiency. In this …
An efficient neural network-based method for patient-specific information involved arrhythmia detection
As researches on computer-aided arrhythmia detection deepen, the application in clinical
practice is still challenging due to weak generalization ability. The utilization of the existing …
practice is still challenging due to weak generalization ability. The utilization of the existing …
Exploration of ECG-based real-time arrhythmia detection: A systematic literature review
Cardiac arrhythmia is a medical term to describe an irregular heartbeat, which occurs when
electrical properties in the heart incapacitated. Although most of arrhythmias are harmless …
electrical properties in the heart incapacitated. Although most of arrhythmias are harmless …
Semantic-aware alignment and label propagation for cross-domain arrhythmia classification
Cross-domain arrhythmia classification (CAC) aims to transfer the model trained on a label-
sufficient source domain to a label-scarce target domain. To the best of our knowledge …
sufficient source domain to a label-scarce target domain. To the best of our knowledge …
An Adaptive Threshold-Based Semi-Supervised Learning Method for Cardiovascular Disease Detection
Deep cardiovascular disease (CVD) detection usually achieves good performance with
large-scale labeled electrocardiograms (ECGs), but manual labeling of ECGs is tedious …
large-scale labeled electrocardiograms (ECGs), but manual labeling of ECGs is tedious …
Universal 12-lead ECG representation for signal denoising and cardiovascular disease detection by fusing generative and contrastive learning
With the wide use of electrocardiogram (ECG) technology, more and more ECGs have been
collected and stored. However, ECG labeling is costly and laborious, the utilization of …
collected and stored. However, ECG labeling is costly and laborious, the utilization of …
A novel lightweight computerized ECG interpretation approach based on clinical 12-lead data
Abstract Although 12-lead electrocardiograms (ECGs) provide a wide range of
spatiotemporal characteristics, interpreting them for arrhythmia detection is difficult due to a …
spatiotemporal characteristics, interpreting them for arrhythmia detection is difficult due to a …