The program leverages the in-context learning abilities of large language models to generate report summaries using domain-specific, individualized data relative to radiology.

A Journal of the American College of Radiology study details how one radiology department  implemented NLP software to resolve inadvertent discordance between physicians and an AI decision support system.

Synoptic radiology reports with detailed information on disease sites in ovarian cancer could help to guide surgical decisions, but they can come at a cost.

With proper training, large language models could help address inappropriate imaging referrals, which are common in EDs, experts write in the Journal of the American College of Radiology.

It has long been known that NPPs increase utilization of radiology services, but new data indicate that they also  are increasingly taking on more imaging interpretation responsibilities.

Automated phone trees are a cost-effective means of reducing unnecessary interruptions and can be implemented “in an easily accessible manner,” according to experts at University Hospitals Cleveland Medical Center.

Three years after the height of COVID forced a global transition to remote work, many professionals are now being called back into the office, including radiologists. 

Large language models could have feasibility in the future as clinical support tools that triage patients for imaging services—with additional updates and more training, of course.