These findings could have positive implications for regions with diverse patient populations, authors of a new analysis suggest.

The incident happened in January of this year, with attackers gaining access to the practice’s systems for five days before they were shut out. 

New findings highlight the  “remarkable potential” of these artificial intelligence tools in improving radiology workflows.  

The solution was developed to be adaptable within the EHR, enabling improved communication of incidental findings beyond just pulmonary nodules to include other high-risk findings. 

Despite this, not all radiologists are on board with routinely using oncology templates.

Generative artificial intelligence models have shown great potential for improving multiple aspects of the radiology field, but a new analysis cautions that they still require significant oversight. 

Digitization of exams has made the imaging industry a “prime target” for cybercriminals, experts wrote recently in the Journal of the American College of Radiology. 

A specialized large language model developed specifically for radiology could be key to helping patients better understand their imaging results.