Nearly 90% of U.S. gastroenterologists are open to using AI for help performing high quality colonoscopies. And of these, 85% believe that computer-assisted polyp detection (CADe) stands to improve their endoscopic performance.

Early this month CMS agreed to reimburse hospitals for using the first AI software to qualify for Medicare’s NTAP mechanism. Healthcare AI watchers have been unpacking the intricacies of the development ever since.

Brainstorming nifty tech tools is only part of the battle to getting them used on the hospital floor. For that a broadly multidisciplinary team in Durham, N.C., has brought aboard some unlikely experts.

Three machine learning algorithms have identified patients likely to suffer extreme pain following surgery with about 80% accuracy each.

A supplier of healthcare software in the respiratory care space has received the FDA’s blessing to market deep learning elements newly added to an existing product.

The company’s work with Anthem-affiliated health plans, in particular, is expected to prosper as a result of this additional funding.

The COVID-19 pandemic is a bad dream in the truest sense of the word—and AI helps to prove it, a team of researchers assert in a study published online Oct. 1 in Frontiers in Psychology.

The work of Regina Barzilay, PhD, a professor of electrical engineering and computer science at MIT, has focused on breast imaging, the development of new antibiotics and much more. 

Researchers at Columbia University have developed a machine learning algorithm that identifies and predicts gender-based differences in adverse reactions to drugs.