Artificial intelligence (AI) is already changing the way health care is provided, with enhanced diagnostic accuracy of images, predictive analyses of patient outcomes from large data sets that can direct treatment plans and analyzing individual patient data to tailor interventions to personal needs. UMass Chan Medical School researcher Feifan Liu, PhD, associate professor of population & quantitative health sciences, is part of a national effort to spearhead another important application: leveraging AI for health equity.

In 2022, Dr. Liu was among the first cohort of leadership fellows in the National Institutes of Health’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Research Diversity (AIM-AHEAD) program, a partnership to enhance participation and representation of researchers and communities underrepresented in the development of AI and machine learning models, and to improve the capabilities of this emerging technology to address health disparities and inequities.

“Feifan’s work with AIM-AHEAD and being part of this AIM-AHEAD structure is leading the way in terms of thinking, not just what the value is of AI, but how does this work in the health care system and society at large?” said Ben S. Gerber, MD, MPH, professor of population & quantitative health sciences, who works with Liu on several projects. “What are the risks? How do we deal with fairness, bias and trust, and other ethical issues of artificial intelligence?”

Research Targets Diabetes and Heart Disease Prevention, Leveraging AI for Health Equity

Liu is principal investigator on two major research initiatives that grew out of the AIM-AHEAD fellowship. The first, DETERMINE (Diabetes Prediction and Equity through Responsible Machine Learning), is a $1.4 million, two-year NIH AIM-AHEAD consortium development grant in partnership with University of Illinois Chicago and Temple University to develop an AI-powered multivariable risk prediction model to integrate social, demographic and clinical factors for accurate, fair, generalizable and interpretable type 2 diabetes prediction. Dr. Gerber is co-principal investigator of the study, now in its second year.

“The main goal is to build a responsive AI model predicting the risk of developing type 2 diabetes and evaluate how well the model generalizes across different institutions as well as how equitably the model performs across different demographic subgroups,” said Liu. “We will also conduct simulation analyses and illustrate the potential impact on real-world clinical practice, and improving access to preventive medicine or prevention programs, especially for minority groups disproportionately affected by type 2 diabetes.”

Read the full article about leveraging AI for health equity by Susan E. W. Spencer at UMass Chan Medical School.