Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Researchers, including the University of Tennessee, Knoxville’s Belinda Akpa, are using predictive modeling and machine ...

Predictive maintenance and digital twin technologies use real-time aircraft data and advanced analytics to help MROs increase ...

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

Delphi-2M was trained on the world's most comprehensive biomedical database with health information from over 400,000 people.

The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission that could reshape how ...

Confronting the governance gap slowing safe and responsible AI adoption in healthcare. Just as CMMI brought discipline ...

When he was just a teenager trying to decide what to do with his life, César de la Fuente compiled a list of the world’s ...

Insulin resistance—when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels—is ...

As integrated health technologies increasingly shape the future of heart failure management, this paper provides ...

According to the working group, the pilot is intended to test whether the tool can effectively explain how insurers manage AI ...

By merging telemetry data with machine learning, the advanced software platform detects issues early, reducing downtime and ...