Cardiovascular

Arrhythmias

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

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A Review on the State of the Art in Atrial Fibrillation Detection Enabled by Machine Learning.

Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the main c...

First-in-man application of a cold ablation robot guided laser osteotome in midface osteotomies.

The aim of the study was to assess the clinical applicability of robot guided laser osteotomy for cl...

In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department.

Background Classical ST-T waveform changes on standard 12-lead ECG have limited sensitivity in detec...

Vascular Aging Detected by Peripheral Endothelial Dysfunction Is Associated With ECG-Derived Physiological Aging.

Background An artificial intelligence algorithm that detects age using the 12-lead ECG has been sugg...

Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1.

Gamma oscillations are thought to play a key role in neuronal network function and neuronal communic...

Discovering and Visualizing Disease-Specific Electrocardiogram Features Using Deep Learning: Proof-of-Concept in Phospholamban Gene Mutation Carriers.

BACKGROUND: ECG interpretation requires expertise and is mostly based on physician recognition of sp...

Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection.

Nowadays, deep learning-based models have been widely developed for atrial fibrillation (AF) detecti...

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HC...

A Head-to Head Comparison of Machine Learning Algorithms for Identification of Implanted Cardiac Devices.

Application of artificial intelligence techniques in medicine has rapidly expanded in recent years. ...

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks.

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a...

Demonstration of the potential of white-box machine learning approaches to gain insights from cardiovascular disease electrocardiograms.

We present the results from a white-box machine learning approach to detect cardiac arrhythmias usin...

Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG.

BACKGROUND: This paper proposes a novel method for automatically identifying sleep apnea (SA) severi...

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram.

INTRODUCTION: Early detection and intervention of atrial fibrillation (AF) is a cornerstone for effe...

Application of a machine learning algorithm for detection of atrial fibrillation in secondary care.

Atrial fibrillation (AF) is the most common sustained heart arrhythmia and significantly increases r...

Estimation of End-Diastole in Cardiac Spectral Doppler Using Deep Learning.

Electrocardiogram (ECG) is often used together with a spectral Doppler ultrasound to separate heart ...

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography.

Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of ...

Deep learning for digitizing highly noisy paper-based ECG records.

Electrocardiography (ECG) is essential in many heart diseases. However, some ECGs are recorded by pa...

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