Black youth are at a higher risk for behavioral health crises than their non-Black peers. Suicide, the severe consequence of behavioral health crises, is a public health concern and is ranked as the second leading cause of death in 10 to 24-year-olds. There is a critical need to deeply understand social risk factors unique to Black youth and their differentiation from risk factors for other racial groups.
Dr. Yifan Peng, assistant professor of population health sciences at Weill Cornell Medicine, along with Dr. Ying Ding, Bill & Lewis Suit Professor at the School of Information at University of Texas at Austin, were awarded a multiple PI $1 million research grant from the National Institutes of Health (NIH) Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program to develop novel interventions targeting risk and protective factors among Black youth with the goal of reducing the suicide rate. The team’s objective is twofold: to develop and validate new AI approaches to identify individual-level social risks of Black youth as well as develop approaches that enhance trust within underserved communities regarding the use of artificial intelligence/machine learning (AI/ML).
Dr. Peng and Dr. Ding are joined by an interdisciplinary team of experts, including Dr. Yunyu Xiao and Dr. Jyoti Pathak from the Department of Population Health Sciences at Weill Cornell Medicine, Dr. Craig Watkins from the Moody College of Communication, and Dr. Yan Leng from McCombs School of Business at The University of Texas at Austin. Additionally, the research team will collaborate with two Historically Black Colleges and Universities (HBCUs), Prairie View A&M and Tuskegee University. This partnership will allow researchers to work with health professionals from historically underrepresented groups to investigate the culturally specific barriers that impact trust and hinder deploying machine learning techniques to address the behavioral health crises among Black youth.