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.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

WPI researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict ...

How predictions would impact clinical decision-making is another question, expert says ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers ...

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.

Climate change, extreme weather events, unprecedented records in temperatures and higher, acidic oceans make it difficult to predict the long-term fate of modern crop varieties. “With these kinds of ...