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, ...

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

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

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, ...

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 ...

Background Physical activity has been associated with neuroprotective and immunomodulatory benefits, potentially influencing ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

Invesco International Small-Mid Company Fund reports Q4 2025 results and strategic shifts. Read the full commentary for ...

An efficient neural screening approach rapidly identifies circuit modules governing distinct behavioral transitions in ...

Background Layoffs may affect the health of those who lose their jobs as well as those who remain employed. Existing studies ...

Our findings indicate that a large commercial insurer is increasingly covering acupuncture for its beneficiaries. Unlike Medicare Part B, which limits acupuncture coverage to chronic low back pain, ...