The method utilizes findings from PET/MR imaging to differentiate between changes in tissue owed to treatment versus tumor progression.

A Signify Research representative highlights key trends in cardiovascular IT systems, including the growing role of AI and much more. 

Harvard radiologists recently created a machine learning model based on the number of unread images, which can accurately predict next-day demand.

The San Francisco-based company says the updates will accelerate radiology workflows by removing administrative burdens and freeing up radiologists to spend more time reviewing imaging exams instead. 

Most patients are first diagnosed with heart failure in an emergency room or hospital, when their symptoms are already severe. This advanced algorithm could change all that by opening up screening to many more patients. 

The question of legal responsibility for AI gone wrong in healthcare remains unsettled. The only sure thing is a lot of finger pointing. 

Wearable health devices outfitted with AI seem poised to transition from consumer novelties to an integral layer of U.S. public-health intelligence. 

Ultromics plans to use the new funds to help expand its presence throughout the United States. In addition, the company is focused on developing additional AI-enabled software offerings.