Many gen AI end users are finding that large language models (LLMs) defy easy infrastructure setup and affordable management costs. One budding option may be to go with small language models (SMLs) instead. 

Harrison.rad.1 can conduct chats related to imaging, identify and localize X-ray findings, generate reports and provide its reasoning based on patient history and clinical context.

If there’s an economic sector whose workforce is largely AI-proof, healthcare is it. 

Just by taking notes during patient visits, generative AI could save a five-physician primary care practice $291,200 in one year. The practice would see a return on its AI investment of 94.13% and reach the breakeven point in a bit more than six months. 

Commercially available software for intracranial hemorrhage detection did not appear to hold up in a prospective, single-center study, experts write in the American Journal of Roentgenology. 

The new partnership is focused on getting advanced AI algorithms into the hands of cardiologists.

An HHS agency is developing ways to keep aging AI-enabled medical devices up to snuff for the long haul. 

Founded in 2020, the acquired firm offers products to aid physicians in assessing and documenting OB/GYN scans, such as prenatal ultrasounds.