Using deep learning models to triage screening mammograms can improve radiologist specificity without hurting sensitivity, according to new research published in Radiology.

Deep learning can be used to triage cancer-free mammograms and improve the efficiency of radiologists, according to an Aug. 6 feasibility study published in Radiology.

Scientists at the University of Houston have developed a wearable device that can gather and transmit enough biometric information to go unnoticed by human wearers and could give robots a virtual sense of touch.

The 2019 Radiological Society of North America (RSNA) annual meeting in Chicago is expanding its artificial intelligence offerings.

Deep learning can improve the accuracy and efficiency of digital breast tomosynthesis (DBT) examinations, according to new findings published in Radiology: Artificial Intelligence.

MRI and CT scans of infants exposed to the Zika virus in the womb revealed a range of brain abnormalities, reported authors of a recent study published in JAMA Network Open. The findings place neuroimaging as an important step in evaluating such patients.

RSNA announced Wednesday, July 31, that it would be expanding its AI Showcase at RSNA 2019 in Chicago.

Utilizing an AI system for digital breast tomosynthesis (DBT) can improve radiologists’ accuracy while dramatically reducing reading times, according to a new study published in Radiology: Artificial Intelligence.