Cardiovascular

Arrhythmias

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

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Showing 1870-1890 of 2,496 articles
DT4ECG: A Dual-Task Learning Framework for ECG-Based Human Identity Recognition and Human Activity Detection

This article introduces DT4ECG, an innovative dual-task learning framework for Electrocardiogram (...

Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model

Electrocardiogram (ECG) is essential for the clinical diagnosis of arrhythmias and other heart dis...

Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements

Catheter ablation of Atrial Fibrillation (AF) consists of a one-size-fits-all treatment with limit...

FADE: Forecasting for Anomaly Detection on ECG

Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early ...

Generation of Drug-Induced Cardiac Reactions towards Virtual Clinical Trials

Clinical trials remain critical in cardiac drug development but face high failure rates due to eff...

Multi-scale Masked Autoencoder for Electrocardiogram Anomaly Detection

Electrocardiogram (ECG) analysis is a fundamental tool for diagnosing cardiovascular conditions, y...

DE-PADA: Personalized Augmentation and Domain Adaptation for ECG Biometrics Across Physiological States

Electrocardiogram (ECG)-based biometrics offer a promising method for user identification, combini...

Explainable and externally validated machine learning for neuropsychiatric diagnosis via electrocardiograms

Electrocardiogram (ECG) analysis has emerged as a promising tool for identifying physiological cha...

Deep learning model for ECG reconstruction reveals the information content of ECG leads

This study introduces a deep learning model based on the U-net architecture to reconstruct missing...

Convolutional Fourier Analysis Network (CFAN): A Unified Time-Frequency Approach for ECG Classification

Machine learning has revolutionized biomedical signal analysis, particularly in electrocardiogram ...

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DCentNet: Decentralized Multistage Biomedical Signal Classification using Early Exits

DCentNet is a novel decentralized multistage signal classification approach designed for biomedica...

High-Accuracy ECG Image Interpretation using Parameter-Efficient LoRA Fine-Tuning with Multimodal LLaMA 3.2

Electrocardiogram (ECG) interpretation is a cornerstone of cardiac diagnostics. This paper explore...

[Application Status of Machine Learning in Assisted Diagnosis Techniques of Cardiovascular Diseases].

In recent years, cardiovascular disease has become a common disease. With the development of machine...

Jan 2025 39993978
DiffuSETS: 12-lead ECG Generation Conditioned on Clinical Text Reports and Patient-Specific Information

Heart disease remains a significant threat to human health. As a non-invasive diagnostic tool, the...

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Optimization of connectome weights for a neural network model generating both forward and backward locomotion in C. elegans

Previous studies tracking the relationship between manipulations of C. elegans neurons and the resul...

TCUP – An Open Access Tool to Predict Tissue of Origin and Cancer of Unknown Primary (CUP)

Cancer of unknown primary (CUP) remains a major diagnostic hurdle, compromising therapies that depen...

Atypical collective oscillatory activity in cardiac tissue uncovered by optogenetics

Many biological processes emerge as frequency-dependent responses to trains of external stimuli. Hea...

A multifaceted approach for obstructive sleep apnea classification from ECG signal using deep learning

Obstructive sleep apnea (OSA) is a common sleep disorder associated with increased cardiovascular an...

Deep learning the dynamic regulatory sequence code of cardiac organoid differentiation

Defining the temporal gene regulatory programs that drive human organogenesis is essential for under...

AI-assisted modeling of attention quantifies engagement and predicts cognitive improvement in older adults

Cognitive training aims to prevent or slow cognitive decline in older adults, but outcomes vary wide...

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