AI shines in radiology when tasked with interpreting images of patients whose odds of illness are either very high or very low. In these cases, the technology could help mitigate burnout and supplement staffing. 

"As the nation’s largest payer of healthcare, Medicare’s policies on coverage and payment for AI technologies are especially critical," AdvaMed says. 

New research in the American Journal of Roentgenology details a deep learning super-resolution image reconstruction technique that opens the door for accelerated imaging of the knee.

"Using a similar approach of front-loaded, declining incentives, an AI-focused program could help accelerate adoption and implementation," write Richard Heller and Nina Kottler. 

However, it’s still uncertain whether the Trump administration will follow through with the new HHS policy update. 

“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care," one expert contends. 

Emory University radiologists recently sought to improve the readability of their recall messages, asking the large language model for help. 

RadNet provides 1.9M mammograms per year in the U.S., and adding iCAD’s installed customer base would boost the number of impacted exams to 10M.