Arrhythmias

Enhancing out-of-hospital cardiac arrest survival in China through the 5-minute social rescue circle implementation.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) survival in China remains critically low due to limited bystander cardiopulmonary resuscitation (CPR) training, insufficient automated external defibrillator (AED) deployment, and delayed community rescue responses. This study quantitatively assessed the impact of the intervention and the 5-minute social rescue circle (5MSRC) on OHCA outcomes in Ba...

In silico prediction of drug-induced cardiotoxicity with ensemble machine learning and structural pattern recognition.

Drug-induced cardiotoxicity poses a significant risk to human health, and reliable predictive models are needed for safety assessment. In this study, a range of machine and deep learning models were developed for five cardiotoxicity end points, including heart failure (HF), arrhythmia (ARR), heart block (HB), hypertension (HP), and heart attack (HA). A total of 110 predictive models were construct...

Fetal arrhythmia detection method based on QCNN-BiLSTM.

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people globally. Cold air exposure is a potential risk facto...

Electrocardiogram-Based Artificial Intelligence for Detection of Low Ejection Fraction: A Contemporary Review.

Artificial intelligence (AI) is transforming the role of electrocardiography (ECG) in cardiovascular care, enabling early disease detection, improved ...

An enhanced deep learning framework for muscle artifact removal from ECG signal integrating resnet, GCAB, and BI-LSTM.

Electrocardiogram (ECG) signals are significantly distorted during recording by muscle artifact (MA), causing signal frequency overlap and making it d...

Prospective Registry Study on Thermal Liver Ablation of Primary and Secondary Liver Tumours Named the A-IMAGIO Study.

PURPOSE: The long-term objective of the Ablation-IMaging and Advanced Guidance for workflow optimization in Interventional Oncology (A-IMAGIO) project...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple health modalities from many individuals. Access to mult...

Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced a...

Stabilization of the human heartbeat using adaptive controller-based optimized deep policy gradient.

Stabilizing the cardiac rhythm is imperative for preserving cardiovascular health and preventing life-threatening arrhythmias. The stabilization of th...

ECG-Based Detection of Acute Myocardial Infarction using a Wrist-Worn Device.

BACKGROUND: A wrist-worn wearable device for acquiring limb and chest ECG leads (wECG) may constitute a promising approach to detection of acute myoca...

Real-time cardiac cine MRI: A comparison of a diffusion probabilistic model with alternative state-of-the-art image reconstruction techniques for undersampled spiral acquisitions.

PURPOSE: Electrocardiogram (ECG)-gated cine imaging in breath-hold enables high-quality diagnostics in most patients but can be compromised by arrhyth...

Artificial Intelligence-Enabled ECG to Detect Congenitally Corrected Transposition of the Great Arteries.

L-loop congenitally corrected transposition of the great arteries (ccTGA) is a rare congenital heart defect that may remain undiagnosed for decades an...

Towards Artificial Intelligence-based Decision Support for Large-scale Screening for Atrial Fibrillation.

Atrial fibrillation is a prevalent cardiac arrhythmia, significantly increasing the risk of stroke, heart failure, and mortality. Early detection, esp...

The 2024 ESC guidelines on atrial fibrillation: essential updates for everyday clinical practice.

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, and it is associated with substantial morbidity, mortality, and economic burden. Ef...

Machine learning application for bleeding risk prediction in patients with atrial fibrillation treated with oral anticoagulation.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with a significantly increased risk of systemic thromboembolism and stroke. Anti...

Current status and challenges of minimally invasive ultrasound thermal ablation technology.

Image-guided minimally invasive ultrasound thermal ablation has been widely studied for disease treatment due to its unique advantages, such as large ...

A multimodal dataset for coronary microvascular disease biomarker discovery.

Coronary microvascular disease (CMD), particularly prevalent among women, is associated with increased morbidity and mortality, making clinical screen...

A hybrid approach for machine learning based beat classification of ECG using different digital differentiators and DTCWT.

This research paper presents a systematic approach to ECG beat classification using advanced machine learning techniques. The study classifies ECG bea...

Atrial Fibrillation Recurrence After Catheter Ablation: The Puzzle We Have and the Pieces We Need.

Atrial fibrillation (Afib) recurrence following catheter ablation (CA) remains a significant challenge within the electrophysiology community, potenti...