Arrhythmias

Arrhythmias and cardiac devices management in oncology patients.

Cardiac arrhythmia is increasingly encountered in patients with cancer, not only as a result of shared risk factors but also as a direct consequence of malignancy and its therapies. This evolving overlap has positioned arrhythmia management as a key component of cardio-oncology practice. This review outlines current strategies for managing atrial and ventricular arrhythmias, conduction disorders, ...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines by persistent (≥3 months) abnormalities of kidney structure or function, including reduced estimated glomerular filtration rate (eGFR) and/or albuminuria, affects 10%-15% of adults worldwide and is a powerful, independent risk factor for cardiovascular diseases, including heart failure (HF). ...

LA-TReQNet: Improving Multielement Quantification Model for Laser Ablation Inductively Coupled Plasma Mass Spectrometry Based on Deep Learning Network.

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a widely used quantitative technique. However, conventional calibration app...

AI-Enhanced ECG Screenings: An Alternative to Traditional Questionnaires for Ischaemic Heart Disease.

Ischaemic heart disease (IHD) is the leading global cause of death. Traditional screening tools like the Framingham Risk Score (FRS) and Systematic Co...

Emerging perspectives in cardiovascular medicine.

Cardiovascular medicine continues to evolve rapidly through advances in molecular biology, biomarkers, digital technologies, and interventional strate...

ECG-Gated Retrospective Coronary CT Angiography With Deep Learning Reconstruction on 8-cm Detector CT Scanners: Pushing Radiation Dose Towards Prospective Acquisition on 16-cm Wide-Detector Scanners.

PURPOSE: Although 16-cm wide-detector CT scanners with prospective ECG-gating enable coronary artery imaging within a single cardiac cycle at a low ra...

Addressing disparities in transthyretin amyloid cardiomyopathy: A systematic review of artificial intelligence in the early identification to improve patient outcomes.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) remains substantially underdiagnosed among Black patient populations. When applied to non-i...

Resuscitation 2025 congress: launch of the resuscitation guidelines, scientific advances, education, equity, and innovation across the chain of survival.

The European Resuscitation Council (ERC) Congress - Resuscitation 2025 was held in Rotterdam as a fully in-person international meeting and served as ...

AI-Enhanced Electrocardiogram for Detection of Occlusive Myocardial Infarction in High-Risk Non-ST-Segment Elevation Acute Coronary Syndrome.

BACKGROUND: Whether an artificial intelligence-enhanced electrocardiogram (AI-ECG) improves detection of occlusive myocardial infarction (OMI) in non-...

Smart Sensors, Smarter Hearts: The Wearable Revolution in Cardiology.

Cardiovascular disease (CVD) continues to claim more lives than any other condition worldwide. Traditional clinic visits capture only brief snapshots ...

Lightweight and interpretable edge intelligence AI with intrusion detection for trustworthy cardiac arrhythmia in medical IoT.

Comparative evaluation of multimodal large language models for diagnostic accuracy in pediatric electrocardiography: a prospective comparative diagnostic accuracy study.

UNLABELLED: We evaluated three multimodal LLMs, ChatGPT (GPT-5.2), Gemini 3, and Microsoft Copilot, in pediatric ECG interpretation, focusing on clini...

Chronic heart failure detection based on long-term RR interval dynamics.

Chronic heart failure (CHF) is a condition affecting millions worldwide, characterized by the heart's reduced ability to pump blood efficiently. Conve...

Multi-domain ECG feature extraction enable accurate automated recognition of bipolar disorder, depression and schizophrenia.

OBJECTIVE: To develop and validate a multi-lead electrocardiogram (ECG)-based machine learning system for automated classification of major psychiatri...

Exploring Deep Learning Models for Small Histopathology Datasets: Segmentation and Classification of Glomerular Crescent Lesions with Ablation, Interpretability, and Calibration Analyses.

Glomerular crescent lesions are critical indicators of severe kidney injury and are closely associated with disease progression. However, their automa...

Transfer learning is the electrocardiogram reconstruction capstone.

Electrocardiogram (ECG) reconstruction from reduced-lead configurations is essential for improving patient comfort and enabling wearable cardiac monit...

Performance of Artificial Intelligence-Powered ECG Analysis in Suspected ST-Segment Elevation Myocardial Infarction.

BACKGROUND: Artificial intelligence (AI)-based electrocardiogram (ECG) analysis has emerged as a promising adjunct to human ECG interpretation in susp...

Electrocardiogram derived heart age models agreement, accuracy and predictive ability in the Tromsø study.

Convolutional neural networks (CNNs) can estimate electrocardiogram (ECG)-based heart age. We compared three published CNNs in the Tromsø Study cohort...

VitalDB Arrhythmia Database: An Anesthesiologist-Validated Large-scale Intraoperative Arrhythmia Dataset with Beat and Rhythm Labels.

Intraoperative cardiac arrhythmias present distinct characteristics compared to non-surgical environments, yet publicly available electrocardiogram (E...

Predicting Recurrence and Outcomes After Stressor-Associated Atrial Fibrillation Using ECG-Based Deep Learning.

BACKGROUND: Stressor-associated atrial fibrillation (AF) refers to new-onset AF that occurs with a reversible, acute stressor. Identifying individuals...