Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk ...

Concept proposes modular building blocks designed to convert local moon dust into protective habitat shielding LAS VEGAS, ...

A tool developed by the American Heart Association (AHA), proven to accurately predict heart disease risk for Americans, can be applied to the global population, a new study led by NYU Langone Health ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

Chronic kidney disease (CKD) and heart failure (HF) share pathophysiological mechanisms, rendering HF one of the most burdensome cardiovascular complication in CKD. Current HF prediction models, ...

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

About half of all American adults grapple with some form of heart disease, so it's understandable to want to do what you can to lower your risk, especially if you have a family history. While eating ...

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...

Copyright: © 2026 The Author(s). Published by Elsevier Ltd. We analyzed data from the J-Proof HF Registry, a nationwide prospective cohort encompassing 96 ...