Cardiovascular

Arrhythmias

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

1,702 articles
Stay Ahead - Weekly Arrhythmias research updates
Subscribe
Browse Specialties
Showing 463-483 of 1,702 articles
A Product Fuzzy Convolutional Network for Detecting Driving Fatigue.

Existing driving fatigue detection methods rarely consider how to effectively fuse the advantages of...

Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease.

BACKGROUND: Information on electrocardiogram (ECG) has not been quantified in obstructive coronary a...

Transformer-based temporal sequence learners for arrhythmia classification.

An electrocardiogram (ECG) plays a crucial role in identifying and classifying cardiac arrhythmia. T...

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms.

BACKGROUND: Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial ...

Erroneous electrocardiographic interpretations and its clinical implications.

INTRODUCTION: The advancement of artificial intelligence (AI) has aided clinicians in the interpreta...

Enhancement of Non-Linear Deep Learning Model by Adjusting Confounding Variables for Bone Age Estimation in Pediatric Hand X-rays.

In medicine, confounding variables in a generalized linear model are often adjusted; however, these ...

A Systematic Survey of Data Augmentation of ECG Signals for AI Applications.

AI techniques have recently been put under the spotlight for analyzing electrocardiograms (ECGs). Ho...

Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time.

With an aging population and increased chronic diseases, remote health monitoring has become critica...

NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to s...

Accuracy of robot-assisted stereotactic MRI-guided laser ablation in children with epilepsy.

OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe...

Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning.

Congenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogr...

ECG-Free Heartbeat Detection in Seismocardiography Signals via Template Matching.

Cardiac monitoring can be performed by means of an accelerometer attached to a subject's chest, whic...

Efficient Deep Learning Based Hybrid Model to Detect Obstructive Sleep Apnea.

An increasing number of patients and a lack of awareness about obstructive sleep apnea is a point of...

In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring.

This work presents an artificial intelligence (AI) framework for real-time, personalized sepsis pred...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality g...

Deep Learning Strategy for Sliding ECG Analysis during Cardiopulmonary Resuscitation: Influence of the Hands-Off Time on Accuracy.

This study aims to present a novel deep learning algorithm for a sliding shock advisory decision dur...

Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams.

Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery,...

Flamingo-Optimization-Based Deep Convolutional Neural Network for IoT-Based Arrhythmia Classification.

Cardiac arrhythmia is a deadly disease that threatens the lives of millions of people, which shows t...

Predicting drug adverse effects using a new Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD).

Electrical data could be a new source of big-data for training artificial intelligence (AI) for drug...

Evaluation of a deep learning-enabled automated computational heart modelling workflow for personalized assessment of ventricular arrhythmias.

Personalized, image-based computational heart modelling is a powerful technology that can be used to...

A new deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognition.

Using ECG signals captured by wearable devices for emotion recognition is a feasible solution. We pr...

Browse Specialties