Latest AI and machine learning research in arrhythmias for healthcare professionals.
BACKGROUND AND OBJECTIVE: Automatic electrocardiogram (ECG) signal analysis for heart disease detect...
OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer ...
AIMS: There is a lack of tools for accurately identifying the risk of readmission for heart failure ...
Cardiac resynchronization therapy (CRT) can lead to marked symptom reduction and improved survival i...
The heart's study holds paramount importance in human physiology, driving valuable research in cardi...
OBJECTIVE: Histotripsy is a focused ultrasound therapy that ablates tissue via the action of bubble ...
Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on h...
Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, ...
PURPOSE OF REVIEW: Artificial intelligence (AI) is transforming electrocardiography (ECG) interpreta...
BACKGROUND: Valvular heart disease (VHD) is becoming increasingly important to manage the risk of fu...
. Electrocardiographic (ECG) lead misplacement can result in distorted waveforms and amplitudes, sig...
Heart failure (HF) encompasses a diverse clinical spectrum, including instances of transient HF or H...
Cardiovascular diagnostics relies heavily on the ECG (ECG), which reveals significant information ab...
To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image rec...
Rapid and accurate electrocardiogram (ECG) signal classification is crucial in high-stakes healthcar...
The rapid growth in computational power, sensor technology, and wearable devices has provided a soli...
OBJECTIVE: Non-sustained supraventricular tachycardia (nsSVT) is associated with a higher risk of de...
Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classi...
Deep neural networks have become increasingly popular for analyzing ECG data because of their abilit...
Deep neural networks (DNNs) are increasingly important in the medical diagnosis of electrocardiogram...
Developing an efficient heartbeat monitoring system has become a focal point in numerous healthcare ...