Latest AI and machine learning research in arrhythmias for healthcare professionals.
Real-time cognitive load assessment is essential for adaptive human-computer interaction but remains...
Circadian behaviors are controlled by dedicated brain pacemaker neurons, whose activity oscillate du...
Delayed diagnosis and poor antiretroviral therapy (ART) adherence remain primary drivers of HIV-rela...
The accurate automated diagnosis of cardiac abnormalities from 12-lead electrocardiograms (ECGs) is ...
Despite the growing success of deep learning (DL) in multivariate time-series classification, such a...
While scaling laws have established a fundamental framework for foundation models in natural languag...
Von Economo neurons (VENs) are selectively lost in behavioural-variant frontotemporal dementia (bvFT...
Electrocardiogram (ECG)-based biometric recognition has emerged as a promising solution for secure a...
Background: Apnoea of prematurity is common and may cause desaturation and/or bradycardia. There is ...
Acoustic monitoring is a scalable approach for assessing bat populations, yet automating the detecti...
Background: Catheter ablation is the most effective rhythm control strategy for atrial fibrillation ...
Rheumatic heart disease (RHD) remains a major public health concern across low- and middle-income co...
Maximal oxygen consumption VO2max is the gold standard for cardiorespiratory fitness but requires re...
Specialized foundation models are beginning to emerge in various medical subdomains, but pretraining...
Objective: How structured clinical features and cluster-semantic embeddings interact under self-dist...
This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that ...
Kawasaki disease (KD) is a systemic vasculitis in young children, and early diagnosis remains challe...
Early detection of Rheumatic Heart Disease (RHD) is essential in reducing its associated mortality a...
Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinically ...
Automated pediatric electrocardiogram (ECG) diagnosis remains challenging because models trained pre...
Deep learning models for 12-lead electrocardiogram (ECG) analysis achieve high diagnostic performanc...