Cancer patients are often expected to wait before starting radiation therapy so that a full treatment plan can be developed. Could AI help prevent such delays? 

AI is making a monumental impact on the way radiologists and other imaging specialists deliver care, but some providers still can’t afford to make the necessary investments at this time.  

When AI first started gaining popularity in healthcare, many providers were critical, skeptical or just avoided learning about the technology altogether. However, according to a new analysis, the time has come for cardiologists to step up and pay close attention.

AI models can be trained to predict outcomes for patients receiving thrombolysis for acute ischemic stroke (AIS), according to a new study published in the Journal of the Neurological Sciences.

The Wuhan coronavirus has already infected thousands of people around the world, with its death toll quickly approaching triple digits. Can AI prove to be a valuable tool in studying the spread of such illnesses?

When research teams are developing deep learning models, they have to make certain decisions about the image resolutions used in their work. For instance, should they always aim to use the largest images possible? Or are there times when smaller images can get the job done?  

Dermatologists need to be more involved in the development of AI technologies designed to evaluate skin cancer, according to a new analysis published in the Journal of the American Academy of Dermatology.

TeachAids, a nonprofit organization focused on health education, has launched a new virtual reality (VR) program that teaches young athletes how to play safe and properly diagnose and treat a concussion.