Among the team’s key findings were that around 10% of infected patients first presented with digestive troubles rather than fever and cough. More striking still, 41% seemed to have become infected within the hospital—and many of these were healthcare workers.

AI models can predict when patients may be at an increased risk of in-hospital mortality, according to new research published in JAMA Network Open. If implemented, such models could be used to help healthcare providers improve decision-making and deliver better patient care.

Caption Health, a California-based AI company, has received authorization from the FDA to market its software solution for acquiring echocardiography images in the United States.

AI algorithms can help radiologists achieve a “significant improvement” in their ability to detect breast cancer, according to a new study published in The Lancet Digital Health.

An AI simulation model predicts catastrophic effects of the novel coronavirus that originated in Wuhan, China, but the credibility of AI models is being called into question.

According to a new AI simulation, the Wuhan coronavirus could kill 52.9 million people within 45 days—and infect 2.5 billion overall.

Machine learning (ML) can provide significant value in the field of palliative care. However, researchers still have a lot of unexplored ground to cover before the technology reaches its full potential.

Chun Yuan, PhD, has received a two-year, $200,000 grant from the American Heart Association’s Institute for Precision Cardiovascular Medicine for his work on using AI to detect blocked arteries and cardiovascular risk.