Researchers at Duke and in Tanzania have developed an algorithm for discerning the extent of a traumatic brain injury (TBI) in a low-resource setting.

Combing through insurance claims and other health data on more than 72 million U.S. residents, a machine learning algorithm was able to quite accurately identify more than 222,000 individuals who have very early stage Alzheimer’s disease.

As medical devices are increasingly being touched by new AI innovations, the FDA will soon have to grapple with reality of regulating “living things” in a new way, according to a report from Roll Call.

The global excitement around healthcare’s embrace of AI and other developing technologies is not misplaced, but it needs to be tempered by an ongoing watchfulness for misuse.

Over the next 50 to 100 years, quantum computing will increasingly automate all manner of healthcare processes while biomaterials and genetic engineering drive regenerative medicine into everyday care.

Technology giant Tencent has begun a clinical trial in London of its AI program to diagnose Parkinson’s disease, Financial Times reported.

There’s a lot of buzz about the applications of AI in the healthcare sector, but the innovations are still in infancy, leaving the potential use––and dangers––of AI in clinical settings unknown.

A machine learning tool for speech analysis has been shown capable of diagnosing childhood depression and anxiety with 80% accuracy.