A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

WPI researchers use machine learning and brain scans to identify age- and sex-specific anatomical patterns that predict ...

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 ...

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.

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 ...

Samsung is set to finally unveil the Galaxy S26 series next week at the Galaxy Unpacked event in San Francisco. Just days before the announcement, a tipster has shared new details about the Galaxy S26 ...

This AI system identifies clinically significant valvular heart disease from stethoscope recordings, achieving near-clinical precision and high sensitivity.