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 ...
Background Patients with heart failure (HF) and severe mitral regurgitation (MR) have poor outcomes. Early identification ...
The GENCOV study developed clinical laboratory‑based risk scores to predict mortality among hospitalized COVID‑19 patients in ...
Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...
Background Despite several intensive interventions, HIV remains a major public health challenge affecting many individuals worldwide and highlighting ongoing gaps in HIV testing. Objectives To assess ...
Introduction Ischaemic heart disease (IHD) remains a leading cause of morbidity and mortality worldwide and poses an ...
A fully integrated substance use disorders emergency department model in Stockholm generates significant post-acute treatment ...
New research shows supervised machine learning models combining Helicobacter pylori genomic data with patient demographics can accurately predict gastric cancer risk.
Introduction Duplicate medical records occur when a single patient is assigned multiple medical record numbers within an ...
Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...
Early sexual activity, often defined as initiation before 16, is a risky behaviour associated with many negative social and health outcomes. Sexual norms restricting sex till marriage have declined in ...
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