The authors tested out a variety of machine learning techniques, including large language models and more traditional algorithms. They focused on data that can be gathered prior to treatment, ensuring cardiologists know as much as possible before the procedure.

Nabil Dib, MD, founder of the International Society for Cardiovascular Translational Research, details resources to help doctors and startups navigate the shift from conducting research to commercializing new products and applications.

Overpromising AI capabilities to hospital stakeholders—now there’s a mistake healthcare AI enthusiasts have been known to make.

For the study, researchers had five diabetes specialists judge precision AI tools developed from a large, longitudinal dataset of patients’ individually expressed needs. 

The newly approved device can be worn for up to a week at a time, with no daily maintenance required, and includes advanced AI algorithms that minimize the risk of false alarms or inappropriate shocks.

This expansion comes alongside a growing trend of patients being given near immediate access to their imaging and radiology reports.

Bill Gates wasn’t just wrong to suggest AI will make physicians unnecessary. He was reckless. 

Healthcare may finally have struck a healthy balance between AI hype and AI reality, according to a report from impartial observers who are also, indirectly at least, healthcare AI stakeholders.