Arrhythmias

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...

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...

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...

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...

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...

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...

GenECG: a synthetic image-based ECG dataset to augment artificial intelligence-enhanced algorithm development.

OBJECTIVES: An image-based ECG dataset incorporating visual imperfections common to paper-based ECGs...

Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence.

BACKGROUND: Structural remodeling of the left atrial appendage (LAA) is characteristic of atrial fib...

Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.

In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment...

Acute myocardial infarction diagnosis: impact of artificial intelligence-powered ECG interpretation.

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 (...

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...

Challenging Black-Box Models: Interpretable Explanations for ECG Classification.

Deep learning methods achieve high performance, while often lacking explainability, hindering applic...

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-...

Developmental and epileptic or epileptic encephalopathy with spike-wave activation in sleep: From the 'functional ablation' model to a neurodevelopmental network perspective.

The interplay between epilepsy and cognition is intricate and multifaceted, particularly in the cont...

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 ...

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...

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

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

Electrocardiographic diagnostic possibilities for atrial fibrillation using artificial intelligence: Differentiation from sinus rhythm and other arrhythmias with the PMcardio app in COVID-19 patients.

BACKGROUND: Artificial intelligence (AI) has shown potential in enhancing ECG analysis, but its accu...

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...

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...