South Korean researchers are working on packing the ability to monitor heart health and detect signs of atrial fibrillation into what might be the smallest cardiology wearable to date: a “smart ring.”

A Los Angeles-based startup, GumGum, has raised $11 million in financing and spun out a new healthcare startup focused on the dental industry, according to TechCrunch.

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.

AI has the potential to disrupt the healthcare industry and improve healthcare outcomes of patients through faster diagnosis and more accurate, targeted treatment. But how AI algorithms are trained needs some improvement, according to Naga Rayapati, founder and CEO/CTO at online marketplace GoGetter, which penned an article for Forbes.

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.

It is well known that AI has the potential to upend several areas of medicine, including targeted treatment and diagnostics. However, a lack of knowledge about AI in the healthcare space could have a negative effect, through the spread of misinformation––and fake news.

Researchers studying the basis of visual recognition in two distinct disciplines—computer science and brain science—have put their heads together to advance both fields at once.