William Hsu, PhD, a biomedical informatician and associate professor of radiology at UCLA, has been named deputy editor for the Radiological Society of North America (RSNA)’s new journal, Radiology: Artificial Intelligence.

Artificial intelligence (AI) models utilizing radiologist-provided BI-RADS classification outperformed methods that did not use them, according to an Oct. 15 study in the Journal of the American College of Radiology.

Artificial intelligence (AI) algorithms perform significantly better when they include the opinions of radiologists, according to a new study published in the Journal of the American College of Radiology.

Using microscopic imaging, researchers from the University of Calgary in Alberta, Canada have shown how the kidneys negatively respond to contrast dyes used during various medical tests and procedures, according to a university press release published Oct. 15.

An artificial intelligence (AI) algorithm developed by Google can help detect metastatic breast cancers with significant accuracy and improve pathologist performance, according to two new studies published in the Archives of Pathology and Laboratory Medicine and the American Journal of Surgical Pathology.

A novel convolutional neural network (CNN) approach could be used to help radiologists improve their classification of osteoarthritis (OA) on knee radiographs, reported authors of a new study published in the Journal of Digital Imaging.

Artificial intelligence (AI) can help radiologists distinguish false-positive mammograms from malignant and negative mammograms, according to new research published in Clinical Cancer Research.

Deep learning may accurately identify false-positive mammograms and distinguish such from images identified as malignant or negative, according to new research published Oct. 11 in the journal Clinical Cancer Research.