Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...

Introduction Ischaemic heart disease (IHD) remains a leading cause of morbidity and mortality worldwide and poses an ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Objectives To describe the incidence, presentation and long-term health outcomes of suicidal thoughts and behaviours (STBs) in children aged 12 years or under. Methods This population-based study ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Objectives To assess health-related quality of life (HRQoL), treatment satisfaction and associated factors among older adults with acute heart failure in Northwest Ethiopia. Design Prospective, ...

In this nationwide cohort study, trans Australians experienced substantially elevated mortality risk. Tailored policy responses are needed to address premature mortality in trans populations.