Latest AI and machine learning research in arrhythmias for healthcare professionals.
BACKGROUND: Intracardiac echocardiography (ICE)-based electroanatomical mapping (EAM) improves procedural efficiency and safety in atrial fibrillation (AF) ablation and remains the standard of care. The CARTOSOUND FAM (AI FAM) module uses a deep-learning algorithm that automates left atrial reconstruction without manual contouring. OBJECTIVE: This study aims to evaluate the one-year outcomes of AI...
BACKGROUND: Low left ventricular ejection fraction (LEF) can progress undiagnosed. Artificial intelligence-based electrocardiogram (ECG-AI) screening may provide a scalable means to detect LEF. OBJECTIVES: The purpose of this study was to validate a complete ECG-AI software as a medical device for LEF detection. METHODS: Four geographically diverse sites in the United States identified patients wi...
PURPOSE: Local tumor progression (LTP) of hepatocellular carcinoma (HCC) after thermal ablation (TA) is related to tumor invasiveness and threaten the...
OBJECTIVE: Identifying the first (S1) and second (S2) heart sounds from phonocardiogram (PCG) signals is an essential step in automating the diagnosis...
OBJECTIVE: Arrhythmia classification from electrocardiograms (ECGs) suffers from high false positive rates and limited cross-dataset generalization, p...
The severe environmental impact of conventional plastic electronics necessitates next-generation wearable devices simultaneously embodying high perfor...
Objective. Fetal and maternal health during pregnancy can be monitored with sensors such as Doppler or scalp fetal ECG. This study focuses on single-c...
Artificial intelligence (AI) in cardiology has evolved from rule-based expert systems to data-driven, learning models that can support diagnostic and ...
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia worldwide, with catheter ablation being an effective yet recurrence-prone treatment...
The electrocardiogram (ECG) is a valuable and non-invasive tool for detecting and preventing arrhythmias. However, in real-world situations, ECG signa...
BACKGROUND: Pulmonary hypertension (PH) carries a significant mortality risk, highlighting the need for improved early detection strategies. This revi...
BACKGROUND: Cardiac resynchronization therapy (CRT) can improve clinical outcomes in patients with dyssynchronous heart failure, but many patients sel...
BACKGROUND AND OBJECTIVE: This systematic review evaluates the current state of Machine Learning (ML) methods for predicting Atrial Fibrillation (AF) ...
BACKGROUND AND OBJECTIVES: Although artificial-intelligence-enhanced electrocardiograms (AI-ECGs) offer prediction and diagnosis capabilities superior...
Atrial electrical remodeling spans molecular, electrical, and structural alterations that shorten refractoriness, facilitate reentry, and ultimately c...
INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...
Photodynamic therapy (PDT) is an emerging approach for tumor treatment, valued for its noninvasive and stimuli-responsive properties. However, its the...
Large Language Models (LLMs) hold significant promise for electrocardiogram (ECG) analysis, yet challenges remain regarding transferability, time-scal...
BACKGROUND: Early structural heart disease (SHD) detection is crucial for improving prognostic outcomes, but widely accessible screening methods are l...
OBJECTIVES: Chemotherapy-induced cardiotoxicity is still a major clinical problem, usually appearing subclinically before structural or symptomatic ca...