Artificial Intelligence | September 2019

Machine learning models can be trained to learn from how radiologists make decisions when interpreting screening mammograms, according to a new study published in the Journal of Digital Imaging. Such research may have a significant impact if used to train specialists.

Machine learning models can be trained to extract immunohistochemical (IHC) characteristics from the imaging results of patients with suspected thyroid nodules, according to new research published in the American Journal of Roentgenology.

New AI-based technology can identify patients at risk of a deadly heart attack years before it happens, according to new findings published in the European Heart Journal.

Researchers have developed a new machine learning system that can help pathologists make more accurate breast cancer diagnoses, sharing their findings in JAMA Network Open.

The United States is a global leader in publishing AI-based radiology research, according to new findings published in the American Journal of Roentgenology.

GE Healthcare and Fujitsu Australia have announced a new collaboration focused on diagnosing and monitoring brain aneurysms using AI.

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

Researchers have developed a convolutional neural network (CNN) that predicts long-term mortality from a single chest x-ray, according to new findings published in JAMA Network Open. 

RBJ sought out a representative sampling of radiologists who are not just talking about AI but already using it to beneficial effect. Here are five highlights from what we found.