Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

The fossilised bones of our ancestors remain silent. So, how can we possibly imagine what our earliest languages sounded like ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

S&P 500 concentration risk is surging—top 10 now 41%. See a quant-optimized 15-stock barbell from Strong Buy picks for better diversification.

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

The experts at irishracing.com have fired up their supercomputer to assess which horse has the best chance of winning the Gold Cup ...

As global energy storage expands toward 741 GWh by 2030, operators face challenges managing retired electric vehicle batteries for grid applications.

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

Whether a smartphone battery lasts longer or a new drug can be developed to treat incurable diseases depends on how stably the atoms constituting the material are bonded. The core of molecular design ...

Share on Pinterest An AI tool may be able to predict GVHD risk, prompting earlier treatment to prevent complications. Image credit: Victor Bordera/Stocksy An AI-based tool may be able to predict the ...