A free web tool known as “Chester the AI Radiology Assistant” can assess a person’s chest X-rays online within seconds, ensuring patients’ private medical data remains secure while predicting their likelihood of having 14 diseases.

Two United Nations agencies have joined forces to create the Focus Group on Artificial Intelligence for Health (FG-AI4H)—a group of global representatives the UN hopes will help shape a streamlined, transparent process for vetting AI technologies in the healthcare space.

Machine learning approaches including deep learning and random forest greatly improved a University of Nottingham team’s ability to predict premature death in a study of half a million U.K. Biobank participants, according to research published in PLOS One.

The Mount Sinai Health System and Germany’s Hasso Plattner Institute (HPI) announced March 29 they’re collaborating to create the joint Hasso Plattner Institute for Digital Health at Mount Sinai, an affiliation the institutions say will combine medicine and tech to deliver powerful digital health tools.

A trio of scientists who laid the groundwork for AI research in the '80s have been named the winners of the 2018 Association for Computing Machinery’s A.M. Turing Award, commonly referred to as the “Nobel Prize of Computing.”

A new AI software can quickly and accurately determine the manufacturer and model of a cardiac rhythm device from an x-ray, possibly speeding up treatment when the devices fail.

An AI model developed by a startup in Kentucky is analyzing insurance claims databases to flag expectant mothers at the greatest risk of giving birth to a preterm baby, Wired reported March 26.

CMS has launched an AI challenge that’s incentivizing innovators to develop solutions for a range of administrative challenges, like predicting unplanned hospital admissions and adverse events, the agency announced March 27.

A machine learning model developed by scientists at Google successfully documented and charted disease symptoms from patient-physician conversations in early tests, but the tech still has a long way to go, according to research published in JAMA Internal Medicine March 25.

An AI-powered intervention supported by Google Glass reinforced facial engagement and emotion recognition in a study of children with autism spectrum disorder (ASD), suggesting the digital approach might be a viable way to support those patients without spending five figures on conventional therapy.