Researchers looked at data from more than 2,500 free-text radiology reports of patients undergoing hepatocellular carcinoma surveillance to determine if an NLP approach could extract clinical data and predict downstream utilization of resources.

Natural language processing (NLP) could help radiology providers anticipate fluctuations in demand and provide faster patient care, according to a new study published in the Journal of the American College of Radiology.

Educating radiologists on ACR-recommended follow-up for incidental adnexal lesions and incorporating such guidelines into normal workflow significantly improved the rate of adherence, reported authors of a Feb. 26 study published in the American Journal of Roentgenology.

“Our results show that worklists organized by relative individual interpretation times can decrease the overall group interpretation time in a multireader setting,” wrote authors of a Feb. 26 study published in the the American Journal of Roentgenology.

Implementing a clinical decision support (CDS) tool increased the overall appropriateness scores of CT and MRI orders, but showed no major difference between the habits of house staff and non-house staff.

Numerous studies have shown that clinical decision support (CDS) can help reduce unnecessary imaging. According to a new study in the American Journal of Roentgenology, however, not enough research has focused on how CDS tools impact less experienced providers such as house staff physicians.

There is an "immaturity" between machines and humans, said Paul J. Chang, MD, of the University of Chicago. Unless radiology departments augment their current IT infrastructure, AI could become another technological-driver of burnout.

The Yale School of Public Health’s Department of Biostatistics has launched a new health informatics division and masters program aimed at using data from electronic health records (EHRs) to advance clinical and public health research.