Cardiovascular

Arrhythmias

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

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Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.

BACKGROUND AND AIMS: Emerging evidence supports artificial intelligence-enhanced electrocardiogram (...

May 2025 39992309
Fine-Grained ECG-Text Contrastive Learning via Waveform Understanding Enhancement

Electrocardiograms (ECGs) are essential for diagnosing cardiovascular diseases. While previous ECG...

Optimized deep residual networks for early detection of myocardial infarction from ECG signals.

Globally, the high number of deaths are happening due to Myocardial infarction (MI). MI is considere...

May 2025 40382575
Artificial Intelligence-Derived Electrocardiographic Age Predicts Mortality in Adults With Congenital Heart Disease.

BACKGROUND: Artificial intelligence (AI) can be used to estimate age from the electrocardiogram (AI-...

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May 2025 40373518
A novel approach for ECG signal classification using sliding Euclidean quantization and bitwise pattern encoding.

This study aims to introduce a novel, computationally lightweight feature extraction technique calle...

May 2025 40358468
IKrNet: A Neural Network for Detecting Specific Drug-Induced Patterns in Electrocardiograms Amidst Physiological Variability

Monitoring and analyzing electrocardiogram (ECG) signals, even under varying physiological conditi...

Classification of multi-lead ECG based on multiple scales and hierarchical feature convolutional neural networks.

Detecting and classifying arrhythmias is essential in diagnosing cardiovascular diseases. However, c...

May 2025 40355498
Investigating the correlation between smoking and blood pressure via photoplethysmography.

Smoking has been widely identified for its detrimental effects on human health, particularly on the ...

May 2025 40355864
Cardiovascular Risk Assessment via Sleep Patterns and ECG-Based Biological Age Estimation.

Understanding the intricate relationship between sleep quality and cardiovascular outcomes opens ne...

May 2025 40429335
Performance of fully automated deep-learning-based coronary artery calcium scoring in ECG-gated calcium CT and non-gated low-dose chest CT.

OBJECTIVES: This study aimed to validate the agreement and diagnostic performance of a deep-learning...

May 2025 40348882
State-of-the-art analysis of electrocardiogram findings in sudden cardiac death.

Sudden cardiac death (SCD) is a significant public health issue, and efforts to prevent it have invo...

May 2025 40348407
Are Wearable ECG Devices Ready for Hospital at Home Application?

The increasing focus on improving care for high-cost patients has highlighted the potential of Hospi...

May 2025 40431777
Cardioformer: Advancing AI in ECG Analysis with Multi-Granularity Patching and ResNet

Electrocardiogram (ECG) classification is crucial for automated cardiac disease diagnosis, yet exi...

Bioimpedance assessment method based on back propagation neural network for irreversible electroporation of liver tissue.

The safety and efficacy of irreversible electroporation (IRE) in tumor therapy has been validated ov...

May 2025 40341694
From Biometrics to Environmental Control: AI-Enhanced Digital Twins for Personalized Health Interventions in Healing Landscapes

The dynamic nature of human health and comfort calls for adaptive systems that respond to individu...

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A Comprehensive Literature Review Discussing Diagnostic Challenges of Prinzmetal or Vasospastic Angina.

This narrative review addresses the diagnostic complexities of vasospastic angina (VSA), also known ...

(1)
May 2025 40486459
ArrhythmiaVision: Resource-Conscious Deep Learning Models with Visual Explanations for ECG Arrhythmia Classification

Cardiac arrhythmias are a leading cause of life-threatening cardiac events, highlighting the urgen...

ALFRED: Ask a Large-language model For Reliable ECG Diagnosis

Leveraging Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) for analyzing me...

ECGDeDRDNet: A deep learning-based method for Electrocardiogram noise removal using a double recurrent dense network

Electrocardiogram (ECG) signals are frequently corrupted by noise, such as baseline wander (BW), m...

xLSTM-ECG: Multi-label ECG Classification via Feature Fusion with xLSTM

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, highlighting the c...

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