Cardiovascular

Arrhythmias

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

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Showing 1660-1680 of 2,496 articles
ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular asses...

A curated reference dataset and deep learning model for multi-lead electrocardiographic interval measurements in UK Biobank

Electrocardiographic (ECG) interval measurements underpin clinical decision-making and large-scale c...

A Reproducible Clinical Decision-Support Suite on MIMIC-IV

Most published clinical-AI results are single models on a single dataset, difficult to reproduce, an...

Retrieval-Warmed Energy-Based Reasoning: A Five-Arm Ablation Methodology for Diffusion-as-Inference on Structured Reasoning Tasks

Warm-started diffusion samplers accelerate iterative inference, but it is rarely clear which part of...

Quantifying Explainable AI-introduced signal noise on ECG data with Spectral Entropy

Explainability techniques are used to assess the output of various deep learning models. This is esp...

Agentic Autodiscovery of Diastolic Dysfunction Phenotypes from Surface Electrocardiogram

Background: Left ventricular diastolic dysfunction (LVDD) is a major determinant of heart failure (H...

Image-based deep learning for emergency electrocardiogram classification

Automated electrocardiogram analysis has advanced largely through digital waveforms, yet many emerge...

Physiology-Aware CNN and Zero-Shot Multimodal LLMs for ECG Image Classification: A Comparative Study

Multimodal large language models (LLMs) are increasingly adopted to interpret 12-lead ECG images, th...

Deep learning-based detection of cessation of breathing in pre-term infants

Apnoea of prematurity is characterised by recurrent episodes of cessation of breathing and remains d...

SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models

Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant...

Wearable-Grade Lead Reduction Disproportionately Degrades ECG AI Performance in Elderly Patients: Evidence from PTB-XL and MIT-BIH

Consumer wearable devices increasingly use single-lead electrocardiograms (ECGs) for cardiac monitor...

Utilising Artificial Intelligence to Identify Ventricular Tachycardia Ablation Targets in Sinus Rhythm

Background and Aims: Machine learning has shown potential in predicting ablation targets for ventric...

A Heterogeneous Graph Neural Network Framework for Multi-Horizon Stroke Mortality Prediction

Background: Machine learning models for stroke mortality prediction typically treat each time horizo...

Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices

Continuous electrocardiography (ECG) monitoring could surface rhythm abnormalities before they escal...

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Using Explainability as a Training-Time Reliability Signal for Efficient ECG Classification

Training deep neural networks for clinical time-series analysis is computationally demanding, yet ma...

Boosting ECG Classification Performance by Pre-training with Synthesized Data

Deep Neural Networks (DNNs) typically require extensive datasets for effective training. In the medi...

A Controlled Audit of Pretraining Contamination in Public Medical Vision-Language Benchmarks

Medical vision-language models (VLMs) are evaluated on public benchmarks whose images and question-a...

Does ECG-Based AI Detect Aortic Stenosis Beyond Conventional LVH Criteria? An Analysis of the CLIDAS Database

Background: Aortic stenosis (AS) is a progressive valvular disease associated with poor prognosis on...

Multivariate Machine Learning Analysis of M-ECG-derived Heart Rate Variability in TBI Veterans, With and Without Comorbid PTSD

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) frequently co-occur in Veteran...

ECG-derived age deviation predicts cardiovascular diseases across lead configurations and cohorts

Cardiovascular diseases (CVDs) remain the primary global health burden, motivating the search for ro...

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