Radiology reports derived from structured brain tumor MRI reporting and data systems (BT-RADS) showed measurable improvements compared to free text reports, according to a new study published in Academic Radiology.

A machine learning algorithm can determine appropriate follow-up imaging based off of radiology reports, according to a new study published in the Journal of Digital Imaging. The technology may eventually be developed to automatically tell if a patient completed their follow-up exam.

Patients would like to maintain some control over what data they share and who they share it with, however, according to results of a new study published in JAMA Network Open.

An audio/visual reporting tool integrated into an emergency department’s musculoskeletal workflow can improve communication between radiologists and referring providers while making imaging findings easier to comprehend.

New research suggests screening kids for cervical spine injury (CSI) risk factors could reduce unnecessary CT scans by 50%, significantly limiting radiation exposure.

“Substantial differences in report structure, content, length, and degree of detail provided by different radiologists can be a source of confusion and frustration for referrers and patients," wrote authors of a new study published in the American Journal of Roentgenology.

Parents of pediatric radiology patients value speed over all other aspects of radiology results reporting, according to findings from a new survey published Aug. 14 in Academic Radiology.

Machine learning algorithms can classify free-text pathology reports at the organ level and are easily interpreted by human readers, according to an Aug. 7 study published in Radiology: Artificial Intelligence.