Arrhythmias

Exploring latent diffusion models for ECG generation on the minute scale.

BACKGROUND AND OBJECTIVE: Artificial Intelligence (AI) models for electrocardiogram (ECG) interpreta...

Multimodal deep learning for acute myocardial infarction detection from 12-lead electrocardiogram: a multi-centre study with cross-hospital validation.

AIMS: Acute myocardial infarction (AMI) remains a leading global cause of mortality, where timely di...

Multi-modal deep-learning troponin prediction from electrocardiograms and demographic data.

AIMS: Electrocardiograms (ECGs) and troponin (Tn) testing are essential tools for the diagnosis and ...

Machine learning-enabled assessment of risk of drug-induced QT prolongation at the time of prescribing.

BACKGROUND: Many medications are associated with long QTc. Current long QTc predictors have limited ...

Real-Time Phase-Contrast Cardiovascular MRI Using a Deep Learning Reconstruction Network With Combined Dictionary Learning and CNN.

PURPOSE: This study aims to develop real-time phase-contrast (PC) cardiovascular MRI with low latenc...

Sleep disturbance recorded via wearable sensors predicts depression severity 9 years later.

BACKGROUND: Major depressive disorder (MDD) is prevalent and poses major public health implications....

Feature extraction and intelligent diagnosis of ECG signals based on KANs and xLSTM.

Cardiovascular disease (CVD) is the top cause of mortality globally, making it crucial to diagnose a...

Image based artificial intelligence-enhanced electrocardiogram prediction of incident atrial fibrillation.

BACKGROUND: Early prediction of atrial fibrillation (AF) is crucial for reducing adverse outcomes. W...

Newton-Puiseux analysis for interpretability and calibration of complex-valued neural networks.

Complex-valued neural networks (CVNNs) are particularly suitable for handling phase-sensitive signal...

GDT-Net: Multi-level feature extraction network for precise diagnosis of atrial and ventricular fibrillation.

Atrial fibrillation (AFIB) and ventricular fibrillation (VFIB) are two critical cardiovascular disea...

GAN-based novel feature selection approach with hybrid deep learning for heartbeat classification from ECG signal.

Heart arrhythmias are one of the most important categories of cardiovascular illness. A heartbeat th...

Deep Learning Predicts Cardiac Output from Seismocardiographic Signals in Heart Failure.

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compr...

Driver Emotion Recognition Using Multimodal Signals by Combining Conformer and Autoformer.

This study aims to develop a multimodal driver emotion recognition system that accurately identifies...

A New Method of Modeling the Multi-stage Decision-Making Process of CRT Using Machine Learning with Uncertainty Quantification.

Current machine learning-based (ML) models usually attempt to utilize all available patient data to ...

ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.

. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate...

Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.

This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Per...

Artificial intelligence-enhanced ECG detection of acute coronary occlusion in chest pain patients with ST-elevation in lead aVR - A direct comparison to conventional ECG criteria.

Machine Learning-Based Prognostic Models for Mortality in Patients Receiving Implantable Cardioverter Defibrillators.

BACKGROUND: Accurately predicting the clinical trajectory of patients with implantable cardioverter-...

Efficient pretraining of ECG scalogram images using masked autoencoders for cardiovascular disease diagnosis.

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, emphasizing the need fo...

Artificial intelligence in cardiac sarcoidosis: ECG, Echo, CPET and MRI.

PURPOSE OF REVIEW: Cardiac sarcoidosis is a form of inflammatory cardiomyopathy that varies in its c...

Enhancing automatic multilabel diagnosis of electrocardiogram signals: A masked transformer approach.

BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) is one of the most important diagnostic tools in c...