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

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.

And the improved scan times did not come at the expense of image quality but, instead, offered improved signal-to-noise ratio, according to a new study in Skeletal Radiology.

The world’s most popular supplier of cloud services has become a dedicated radiology vendor.

Breast radiologists are known to have higher rates of burnout in comparison to many of their peers, but the beginning of the pandemic brought this group something not often encountered within the specialty—downtime. 

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.

What’s more, the model proved beneficial in a large, diverse cohort that included women with benign breast disease and BRCA mutations.

Given the similarities in accuracy between pathology results and preoperative imaging, MRI could have a greater role in risk assessments in the future, experts suggested in AJR.

Although the predictive power of radiomics has been touted as a tool that could improve patient outcomes, the method has a long way to go before it can be reliably introduced into real-world clinical environments.

The new discovery contradicts the notion that copper is not suitable for use in contrast media.