RSNA 2019 in Chicago is just days away, and the continued evolution of AI in radiology promises to be one of the hottest topics of the entire conference.

Deep learning models can be trained to predict lymph node metastasis in breast cancer patients, according to new findings published in Radiology.

AI can provide significant value to radiologists by sending urgent imaging studies to the top of their worklists, according to a new analysis published in Academic Radiology.

The rise of AI is one of radiology’s biggest trends of the last decade, a move that has energized some radiologists while worrying others.

The rapid rise of AI could potentially change healthcare forever, leading to faster diagnoses and allowing providers to spend more time communicating directly with patients. According to a new report from the Brookings Institution, however, there are also risks associated with AI in healthcare that must be addressed.

Electronic health records received an 'F' rating from Yale researchers who analyzed and rated the technologies on quality and efficiency.

Google was hoping to release a massive dataset of chest x-rays to the public in 2017, but had to cancel at the last minute after receiving an urgent call from the National Institutes of Health (NIH).   

Following up with heart patients via computer or smartphone helped facilitate communication between patients, families and care teams in a small-scale study out of Children’s National Hospital in Washington, D.C.