AI trained with less than 1,000 CT scans may solve 'black box' challenge

Using less than 1,000 imaging cases, researchers from Massachusetts General Hospital (MGH) in Boston were able to train an artificial intelligence (AI) algorithm to detect intracranial hemorrhage (ICH) and classify its five subtypes on unenhanced head CT scans, according to research published in the journal Nature Biomedical Engineering.

Chest imaging in the ED has increased substantially over the last 20 years

A multi-institutional team of researchers found that emergency department (ED) utilization of chest imaging has grown substantially in the U.S. over the last two decades and is likely due to an increased availability of CT scanners and increased pressure on ED physicians to rapidly triage patients, according to a study published Jan. 2 in the Journal of the American College of Radiology.