Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

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

Tiny RNA molecules carried by extracellular vesicles in the bloodstream can accurately predict kidney function decline and cardiovascular risk in chronic kidney disease (CKD), as reported by ...

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 ...

Juntendo University researchers have trained a machine learning algorithm to use clinical information and physical function ...

Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

February is national American Heart Month and the American Heart Association is spotlighting cardiovascular disease and the need for more lifesavers. This year, the association’s message is anyone can ...