Using a mixed-reality holographic computer headset, neurosurgeons can more accurately perform external ventricular drain (EVD) insertion, according a new study out of Beijing published in the Journal of Neurosurgery.

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.

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.

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.

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.

A team of California researchers used a deep convolutional neural network (DCNN) to accurately diagnose traumatic pediatric elbow joint diffusion, according to an Oct. 9 study published in the American Journal of Roentgenology.

A new artificial intelligence (AI) algorithm developed by Canadian researchers can detect evidence of cognitive decline in brain MRI scans, genetics and clinical data, and may predict whether findings will lead to Alzheimer’s disease five years before symptoms appear.