Researchers in Australia are about to begin testing, in humans, a brain-computer interface created to restore communication in people with severe paralysis.  

Auditory specialists placing Cochlear implants in hearing-impaired patients may position the devices better with an assist from AI than with conventional methods. 

Riverain Technologies, a provider of clinical AI software, is receiving a $15 million infusion of investment funding led by Ping An Insurance Company’s Ping An Global Voyager Fund.

Portable ultrasound maker Fujifilm SonoSite has turned to the nonprofit Allen Institute for Artificial Intelligence’s AI2 Incubator for help harnessing AI’s image-interpretation potential.

Jvion, an AI-enabled prescriptive analytics company that aims to prevent harms, has joined ranks with integrated care network Novant Health to become the first member of the Novant Health Institute of Innovation & Artificial Intelligence.

Machine learning analysis of Raman hyperspectroscopy—a technology used to measure the intensity of scattered laser light—has shown strong potential as a screening tool for Alzheimer’s disease when applied to an easily obtainable lab specimen: saliva.

There’s plenty of research into the diagnostic accuracy of medical smartphone apps created to supply clinical decision support (CDS). However, few studies have looked at how helpful these apps are in clinical practice.

International investment firm Morgan Stanley believes odds are strong that Apple will become a major player in healthcare AI, according to an article published Sept. 16 in AppleInsider.

The chances of surviving oral cancer can now be predicted from AI algorithms by measuring immune cells in tumors.

Emerging technologies like AI and robotics have vast potential to improve healthcare. Few question this. What remains unclear is how meaningful the advances will be to healthcare providers and, more to the point, the patients they serve.

The Mayo Clinic has selected Google Cloud to anchor its digital development over the next 10 years.

Geisinger has tapped IBM’s AI expertise and come up with a way to predict hospital patients’ risk of sepsis. In the process, the method can increase chances of survival in those who have the tricky and potentially life-threatening condition.