Researchers will use AI to predict who may develop certain rare diseases

A team of researchers from University of Florida Health and Penn Medicine is using a set of artificial intelligence-powered algorithms called PANDA to find rare “zebras” in patient medical records and help patients affected by certain rare diseases get diagnosed and treated more quickly.

In health care circles, rare diseases are sometimes referred to as ‘zebras’ because they are so unusual and unexpected. Any disease that affects fewer than 200,000 people nationwide is considered a rare disease. Worldwide, there are about 7,000 known rare diseases. In the United States, the total number of people affected by these conditions is about 10%.

Because the symptoms of rare diseases are often vague and perplexing and because so few people are affected, diagnosing them can be difficult, according to Jiang Bian, Ph.D., a professor in the College of Medicine at the University of Florida and chief data scientist for University of Florida Health.

For this reason, Bian said, “Some patients with rare diseases may go undiagnosed and untreated for years.” Bian is part of a team of researchers from UF Health and the Perelman School of Medicine at the University of Pennsylvania that is using artificial intelligence and electronic health records to develop an alert system that will sound the alarm for doctors whose patients appear likely to develop certain rare diseases.

With a funding award of $4.7 million from the National Institutes of Health, the researchers will develop a set of algorithms powered by machine learning, a form of artificial intelligence, to identify which patients are at risk of five different types of vasculitis and two different types of spondyloarthritis, including psoriatic arthritis and ankylosing spondylitis. These predictions, derived from information already available in patients’ electronic health records, could greatly increase the chance of patients being diagnosed sooner.

Read more on the UF Health news site.

Diana Tonnessen October 25, 2022