Healthcare executives have big plans for technology in their revenue cycle management operations. 

Although AI implementation in clinical practice has taken flight in recent years, opportunistic screening utilization has been less common.

The administration has now authorized a total of 69 medical products that incorporate AR/VR since 2015, including 28 in radiology. 

The U.S. Commerce Department wants proof of strong safety and security measures from AI developers and cloud suppliers. 

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.