Cardiovascular

Arrhythmias

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

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Showing 127-147 of 1,699 articles
Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.

Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its lin...

Classifying metro drivers' cognitive distractions during manual operations using machine learning and random forest-recursive feature elimination.

Metro drivers are more likely to trigger accidents if they suffer from cognitive distractions during...

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device...

Deep Learning-Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study.

BACKGROUND: In-hospital cardiac arrest (IHCA) is a severe and sudden medical emergency that is chara...

Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the...

An advanced robotic system incorporating haptic feedback for precision cardiac ablation procedures.

This study introduces an innovative master-slave cardiac ablation catheter robot system that employs...

Author name disambiguation based on heterogeneous graph neural network.

With the dramatic increase in the number of published papers and the continuous progress of deep lea...

Deep Learning Approach for Automatic Heartbeat Classification.

Arrhythmia is an irregularity in the rhythm of the heartbeat, and it is the primary method for detec...

The Evolving Paradigm of Myocardial Infarction in the Era of Artificial Intelligence.

The classification and treatment of myocardial infarction (MI) have evolved significantly over the p...

EffNet: an efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments.

Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case ...

Ventricular Arrhythmia Classification Using Similarity Maps and Hierarchical Multi-Stream Deep Learning.

OBJECTIVE: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We a...

AI-Cirrhosis-ECG (ACE) score for predicting decompensation and liver outcomes.

BACKGROUND & AIMS: Accurate prediction of disease severity and prognosis are challenging in patients...

Protocol for AI-based segmentation and quantification of interstitial cells of Cajal in murine gastric muscle.

Interstitial cells of Cajal (ICCs), pacemaker and neuromodulator cells in the gastrointestinal (GI) ...

Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac ...

Temporal and spatial self supervised learning methods for electrocardiograms.

The limited availability of labeled ECG data restricts the application of supervised deep learning m...

Automated Process for Monitoring of Amiodarone Treatment: Development and Evaluation.

BACKGROUND: Amiodarone treatment requires repeated laboratory evaluations of thyroid and liver funct...

Antifreezing Ultrathin Bioionic Gel-Based Wearable System for Artificial Intelligence-Assisted Arrhythmia Diagnosis in Hypothermia.

Cardiovascular disease (CAD) is a major global public health issue, with mortality rates being signi...

Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning.

To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery ...

Thermo-responsive and phase-separated hydrogels for cardiac arrhythmia diagnosis with deep learning algorithms.

Adhesive epidermal hydrogel electrodes are essential for achieving robust signal transduction and ca...

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