Abstract: With the rise of wearable sensors and smart devices, human activity recognition (HAR) has become a vital research area in ubiquitous computing. Although many studies report high accuracy ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to ...

Background The National Heart Failure Audit gathers data on patients coded at discharge (or death) as having heart failure as ...

Objective Anxiety affects up to one-third of adults with asthma and is linked to poorer disease outcomes and reduced quality ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

Objective To examine whether a multicomponent commercial fitness app with very small (‘micro’) financial incentives (FI) ...

Abstract: The validation of Electromagnetic Transients (EMT) models is essential for ensuring the accuracy of grid compliance and stability studies. However, there is still room for improvement in ...

Objectives This study aimed to identify intraoperative and perioperative factors influencing 30-day mortality after cardiac surgery and to develop a risk score (POP-score) for its prediction. Design ...

Background: Diabetic foot ulcer (DFU) is a common and serious complication in patients with diabetes, which affects the quality of life greatly as well as brings high risk for mortality.