MedStar Health and Georgetown University Medical Center to Develop AI and Machine Learning Training for Early Career and Minority Investigators Interested in Health Disparities
The initiative is part of the NIH-funded AIM-AHEAD Consortium dedicated to addressing the lack of diversity in the field of data science
WASHINGTON (December 20, 2021) — MedStar Health and Georgetown University Medical Center announce their collaboration in the Data Science Training Core, part of a new two-year, multimillion-dollar award funded by the National Institutes of Health (NIH). The initiative is one of the four core functions of the Artificial Intelligence/Machine Learning (AI/ML) Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program.
While the widespread adoption of electronic health records has offered exponential opportunities to apply data science to biomedical research, many challenges remain in accessing the full potential of this data, including access to AI/ML technology, proper training and, most urgently, a lack of diversity in investigators in the field and the data itself. NIH created the AIM-AHEAD program to enhance participation of underrepresented minorities in AI/ML research.
“Artificial intelligence and machine learning are critical tools for research. Ensuring that investigators from all backgrounds and communities have access to learning these skills is essential for supporting an equitable workforce who can contribute to addressing the field’s most pressing questions, ” says Nawar Shara, PhD, director for the Center of Biostatistics, Informatics, and Data Science (CBIDS) at MedStar Health Research Institute, and co-principal investigator for the Data Science Training core.
“In addition to diversifying those contributing to this critical area of work, we are obligated to do all we can to reduce bias on the front end as we’re developing artificial intelligence as that is critical to how AI is applied in medicine and beyond,” explains Peter McGarvey, PhD, professor of biochemistry, molecular and cell biology at Georgetown University Medical Center and director of its Innovation Center for Biomedical Informatics (ICBI).
Shara and McGarvey will develop data science training for early career and minority investigators with a particular interest in advancing health equity. While the initial effort will be to identify training needs to support workforce development, it will be followed by the development of practicums in competencies such as cloud computing, distributed computing, biostatistics, modeling, epidemiology, biomedical informatics and other community-engaged research methods. Alex Libin, PhD, scientific director of simulation education research for MedStar Health Research Institute and associate professor of rehabilitation medicine at Georgetown University Medical Center, will serve as communication and outreach lead for the initiative, bringing his expertise in autonomous learning and digital technology and psychosocial functioning to the team of investigators.
The initial phase of the two-year project is currently underway and will lead to the launch of a suite of training resources and curriculum. The Data Science Training Core team will also provide one-on-one, small and larger group sessions. Training candidates will range from high school, college and graduate students to PhD and postdoctoral fellows.
An important feature of the program is that it represents a collaborative effort across MedStar Health Research Institute, Georgetown University and Howard University — members of the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS) — in collaboration with the University of Maryland.
Joseph Verbalis, MD, professor of medicine at Georgetown University Medical Center and Georgetown director of GHUCCTS, notes that “bringing together a diverse group of accomplished investigators and educators for this unique collaborative training effort across our GHUCCTS institutions reflects the value of the Clinical and Translational Science Award (CTSA) program to stimulate innovative research and educational programs to improve the health of our communities.”
“Advances in machine learning are powering a faster and, critically, a more representative body of medical research,” says Neil J. Weissman, MD, FACC, FASE, chief scientific officer at MedStar Health and president of MedStar Health Research Institute. “It’s vitally important that we work to make the field of data science more inclusive to foster the next generation of investigators who will reshape the future of health care.”
In addition to a focus on developing data science curriculum, the AIM-AHEAD program will include efforts to identify additional research priorities and build out software infrastructure to facilitate AI/ML and health disparities research. Other collaborating institutions in the consortium include National Alliance Against Disparities in Patient Health, Harvard Medical School, Johns Hopkins University, Meharry Medical College, Morehouse School of Medicine, OCHIN, University of Colorado Anschutz Medical Campus, University of Houston, UCLA, The University of North Texas and Vanderbilt University Medical Center.