Latest AI and machine learning research in arrhythmias for healthcare professionals.
CT metal artefact reduction (MAR) methods based on supervised deep learning are often troubled by do...
Catheter ablation (CA) is considered as one of the most effective methods technique for eradicating ...
Emergency department (ED) triage scale determines the priority of patient care and foretells the pro...
With the increased availability of magnetic resonance imaging (MRI) and a progressive rise in the fr...
Arrhythmias using electrocardiogram (ECG) signal is important in medical and computer research due t...
Little is known about electrocardiogram (ECG) markers of Parkinson's disease (PD) during the prodrom...
Due to the tremendous growth of the Internet of Things (IoT), sensing technologies, and wearables, t...
PURPOSE: To compare the oncological and perioperative outcomes of robot-assisted partial nephrectomy...
BACKGROUND: Premature ventricular complexes (PVCs) are prevalent and, although often benign, they ma...
Arrhythmia detection from ECG is an important area of computational ECG analysis. However, although ...
Versatile and energy-efficient neural signal processors are in high demand in brain-machine interfac...
OBJECTIVE: To evaluate transperineal laser ablation (TPLA) with Echolaser® (Echolaser® TPLA, Elesta ...
Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a cruc...
. Although deep learning-based current methods have achieved impressive results in electrocardiograp...
Obstructive sleep apnea (OSA) has a heavy health-related burden on patients and the healthcare syste...
Due to the phenomenon of "involution" in China, the current generation of college and university stu...
This study presents an innovative end-to-end deep learning arrhythmia diagnosis model that aims to a...
Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for patients. H...
Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categori...
OBJECTIVE: Over the past few years, deep learning (DL) has been used extensively in research for 12-...
Existing driving fatigue detection methods rarely consider how to effectively fuse the advantages of...