The Mark Foundation for Cancer Research (MFCR) has contributed funding to eight different research projects that involve AI.

Ensemble learning—the combination of multiple AI models into a single model with a single purpose—can lead to better overall results, according to new research published in Radiology: Artificial Intelligence.

The United States is expected to experience a massive shortage of psychiatrists within the next five years. According to some researchers, however, AI technology could ease some of that burden.

Lunit, a medical software company based out of South Korea, has gained CE certification for its newest chest x-ray analysis solution, Lunit INSIGHT CXR.

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 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.