Latest AI and machine learning research in arrhythmias for healthcare professionals.
In this paper we develop statistical algorithms to infer possible cardiac pathologies, based on data...
Artificial intelligence (AI) is developing rapidly in the medical technology field, particularly in ...
Deep neural networks (DNN) are state-of-the-art machine learning algorithms that can be learned to s...
The purpose of thermal ablation is induction of tumor death by means of localized hyperthermia resul...
Atrial fibrillation is the most common arrhythmia and is associated with high morbidity and mortalit...
BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardi...
The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LV...
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces ...
Atrial fibrillation (AF) is a cardiac arrhythmia which is characterized based on the irregsular beat...
The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whol...
This study attempted to multimodally measure mental workload and validate indicators for estimating ...
BACKGROUND: To evaluate the feasibility and safety of a robot-guided irreversible electroporation (I...
Protein secondary structure prediction remains a vital topic with broad applications. Due to lack of...
Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive...
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomn...
PURPOSE: Twin-to-twin transfusion syndrome (TTTS) is a placental defect occurring in monochorionic t...
The measurement of human vital signs is a highly important task in a variety of environments and app...
Automated electrocardiogram (ECG) analysis for arrhythmia detection plays a critical role in early p...
The automatic detection of atrial fibrillation (AF) is crucial for its association with the risk of ...
The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accura...
Deep learning models have become a popular mode to classify electrocardiogram (ECG) data. Investigat...