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.

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.

Researchers have developed a multitask deep learning model that can effectively assess signs of hip osteoarthritis in x-rays, sharing their findings in Radiology.

The rise of AI in healthcare—especially radiology—has launched countless conversations about ethics, bias and the difference between “right” and “wrong.”