Cardiovascular

Arrhythmias

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

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Showing 1345-1365 of 2,005 articles
Masked Autoencoders that Feel the Heart: Unveiling Simplicity Bias for ECG Analyses

The diagnostic value of electrocardiogram (ECG) lies in its dynamic characteristics, ranging from ...

InsertRank: LLMs can reason over BM25 scores to Improve Listwise Reranking

Large Language Models (LLMs) have demonstrated significant strides across various information retr...

Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection

Electrocardiography (ECG) signals are often degraded by noise, which complicates diagnosis in clin...

Deep Learning-Based Digitization of Overlapping ECG Images with Open-Source Python Code

This paper addresses the persistent challenge of accurately digitizing paper-based electrocardiogr...

An epidemiological knowledge graph extracted from the World Health Organization's Disease Outbreak News.

The rapid evolution of artificial intelligence (AI), together with the increased availability of soc...

Jun 2025 40494870
Heartcare Suite: Multi-dimensional Understanding of ECG with Raw Multi-lead Signal Modeling

We present Heartcare Suite, a multimodal comprehensive framework for finegrained electrocardiogram...

Heart Rate Classification in ECG Signals Using Machine Learning and Deep Learning

This study addresses the classification of heartbeats from ECG signals through two distinct approa...

Near-term prediction of sustained ventricular arrhythmias applying artificial intelligence to single-lead ambulatory electrocardiogram.

BACKGROUND AND AIMS: Accurate near-term prediction of life-threatening ventricular arrhythmias would...

Jun 2025 40157386
Uncertainty-Aware Multi-view Arrhythmia Classification from ECG

We propose a deep neural architecture that performs uncertainty-aware multi-view classification of...

anyECG-chat: A Generalist ECG-MLLM for Flexible ECG Input and Multi-Task Understanding

The advent of multimodal large language models (MLLMs) has sparked interest in their application t...

Full duty cycle laser ablation plasma spectrometry (LAPS) combining a hollow-core toroidal coil with artificial intelligence classification.

The use of a hollow-core toroidal coil (HTC) as an induction detector allows for the analysis of ion...

Jun 2025 40476855
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction.

Heart failure (HF) poses a significant public health challenge, with a rising global mortality rate....

Jun 2025 40524840
Cardiac Phase Estimation Using Deep Learning Analysis of Pulsed-Mode Projections: Toward Autonomous Cardiac CT Imaging.

Cardiac CT plays an important role in diagnosing heart diseases but is conventionally limited by its...

Jun 2025 40031322
AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes.

The performance and long-term health of athletes are significantly influenced by their cardiovascula...

Jun 2025 40216258
Faster R-CNN approach for estimating global QRS duration in electrocardiograms with a limited quantity of annotated data.

In electrocardiography (ECG), measurement of QRS duration (QRSd) is crucial for diagnosing condition...

Jun 2025 40286493
QRS-centric beat-wise atrial fibrillation detection in ECG signals using deep neural networks.

We propose a deep learning approach for beat-wise atrial fibrillation (AF) detection in electrocardi...

Jun 2025 40378565
A multi-scale convolutional LSTM-dense network for robust cardiac arrhythmia classification from ECG signals.

Cardiac arrhythmias are irregular heart rhythms that, if undetected, can lead to severe cardiovascul...

Jun 2025 40233677
Portable ECG and PCG wireless acquisition system and multiscale CNN feature fusion Bi-LSTM network for coronary artery disease diagnosis.

Coronary artery disease (CAD) is a major cause of mortality, especially among aging populations, mak...

Jun 2025 40239232
Fusion of multi-scale feature extraction and adaptive multi-channel graph neural network for 12-lead ECG classification.

BACKGROUND AND OBJECTIVE: The 12-lead electrocardiography (ECG) is a widely used diagnostic method i...

Jun 2025 40184850
Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects.

Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnos...

Jun 2025 38953953
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