Candice Adams-Mitchell receives NIH fellowship created to improve diversity among leaders in AI

Dr. Candice Adams-Mitchell
Dr. Candice Adams-Mitchell

Candice J. Adams-Mitchell, SLP.D., CCC-SLP, a clinical assistant professor in the University of Florida College of Public Health and Health Professions department of speech, language, and hearing sciences, has been awarded a leadership fellowship from the National Institutes of Health’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity program, or AIM-AHEAD.

The goal of the leadership fellowship program is to prepare leaders who champion the use of artificial intelligence and machine learning in addressing persistent health disparities. PHHP boasts two recipients of the inaugural AIM-AHEAD fellowship cohort. In addition to Adams-Mitchell, Shantrel Canidate, Ph.D., M.P.H., an assistant professor of epidemiology, has received a research fellowship.

Adams-Mitchell’s research focuses on examining racial and ethnic disparities in neurological health outcomes among marginal populations of color, specifically African Americans living with heart, lung and blood disorders, such as sickle cell disease.

“My long-term research career goal is to become an independent health disparities researcher with expertise examining the intersectionality of public health, neurological health outcomes and sickle cell disease,” said Adams-Mitchell, who serves as the equity advisor for the UF Health AI Steering Committee.

The year-long fellowship offers Adams-Mitchell mentorship from AIM-AHEAD core members as well as the opportunity to conduct research using a dataset that includes data from 155 health systems across 28 states representing nearly 5 million patients. Mattia Prosperi, Ph.D., a UF professor of epidemiology and PHHP’s coordinator of artificial intelligence, will serve as Adams-Mitchell’s institutional mentor.

“I will use the resources and trainings made available to me during this fellowship to use large-scale EHR databases for prognostic, diagnostic and treatment outcome prediction studies,” Adams-Mitchell said. “I hope to leverage AI to develop bias-free models to identify interventions and strategies suitable for reducing racial disparities in neurological health outcomes related to communication, cognition and swallowing among individuals living with sickle cell disease.”