Cardiovascular

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

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Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

Early time series classification predicts the class label of a given time series before it is comple...

Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications.

Analog-to-feature (A2F) conversion based on non-uniform wavelet sampling (NUWS) has demonstrated the...

Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals.

Heart diseases are leading to death across the globe. Exact detection and treatment for heart diseas...

A multi-module algorithm for heartbeat classification based on unsupervised learning and adaptive feature transfer.

The scarcity of annotated data is a common issue in the realm of heartbeat classification based on d...

CLINet: A novel deep learning network for ECG signal classification.

Machine learning is poised to revolutionize medicine with algorithms that spot cardiac arrhythmia. A...

Identification of high-risk imaging features in hypertrophic cardiomyopathy using electrocardiography: A deep-learning approach.

BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) are at risk of sudden death, and individ...

A machine learning approach to differentiate wide QRS tachycardia: distinguishing ventricular tachycardia from supraventricular tachycardia.

BACKGROUND: Differential diagnosis of wide QRS tachycardia (WQCT) has been a challenging issue. Publ...

Automatic prediction of obstructive sleep apnea event using deep learning algorithm based on ECG and thoracic movement signals.

BACKGROUND: Obstructive sleep apnea (OSA) is a sleeping disorder that can cause multiple complicatio...

A novel deep learning approach for early detection of cardiovascular diseases from ECG signals.

Cardiovascular diseases, often asymptomatic until severe, pose a significant challenge in medical di...

Long-term results of ablation index guided atrial fibrillation ablation: insights after 5+ years of follow-up from the MPH AF Ablation Registry.

BACKGROUND: Catheter ablation (CA) for symptomatic atrial fibrillation (AF) offers the best outcomes...

Heart failure classification using deep learning to extract spatiotemporal features from ECG.

BACKGROUND: Heart failure is a syndrome with complex clinical manifestations. Due to increasing popu...

Quest for the ideal assessment of electrical ventricular dyssynchrony in cardiac resynchronization therapy.

This paper reviews the literature on assessing electrical dyssynchrony for patient selection in card...

Model-based estimation of AV-nodal refractory period and conduction delay trends from ECG.

Atrial fibrillation (AF) is the most common arrhythmia, associated with significant burdens to pati...

Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina.

Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race,...

ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning.

ECG beat classification or arrhythmia detection through artificial intelligence (AI) is an active to...

Multichannel high noise level ECG denoising based on adversarial deep learning.

This paper proposes a denoising method based on an adversarial deep learning approach for the post-p...

Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable ...

Pre-Processing techniques and artificial intelligence algorithms for electrocardiogram (ECG) signals analysis: A comprehensive review.

Electrocardiogram (ECG) are the physiological signals and a standard test to measure the heart's ele...

Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel artificial intelligence algorithm.

BACKGROUND: Multiple smart devices capable of automatically detecting atrial fibrillation (AF) based...

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