NIH OBSSR Director’s Webinar: Leveraging Advanced Analytics and Data-Driven Artificial Intelligence Technologies to Address the Social and Behavioral Determinants of Health Equity


Irene Dankwa-Mullan MD, MPH

Presenter: Irene Dankwa-Mullan MD, MPH
Head of Health Equity and Deputy Director of Health
IBM Watson Health,
IBM Corporation


This presentation will describe the role of advanced data-driven analytics leveraging artificial intelligence (AI) technologies to provide health equity insights. The conference will include the current use of these AI-based technologies, including tools that have been implemented to deal with the COVID-19 pandemic. These technologies are used in preclinical research, drug discovery, clinical pathway development, risk prediction algorithms, population-level surveillance, and analytics, among others. The drivers of these efforts include comprehensive and massive amounts of data from heterogeneous sources. The technologies have enormous potential to improve current precision medicine and health equity efforts, but they also have the potential to exacerbate existing health disparities without a thoughtful, transparent and inclusive approach, which includes the combats bias in the design, development and implementation of technology. The discussion will focus on the applications of the social and behavioral determinants of health. Finally, the presentation will include potential opportunities for collaborative research partnerships to advance efforts in the behavioral and social science community.


Dr. Irene Dankwa-Mullan is a nationally recognized physician and industry scientist, health equity thought leader, academic, and author with over 20 years of diverse leadership experience. local, regional, national and global in health systems, businesses and the community. She is currently Chief Health Equity Officer, Deputy Chief Health Officer at IBM Watson Health. She is a member of the IBM Industry Academy, a select community of preeminent leaders to drive innovation and engage in cutting-edge endeavors. His current research endeavors to develop and evaluate datasets (real world data), algorithms as well as inclusive technologies – technologies based on artificial intelligence (AI) and machine learning (ML) to empower healthcare providers, patients and their families. A priority is to advance technologies to promote social good and equity. It supports inclusive and participatory engagement with communities and stakeholders. It helps teams model complex decisions associated with health equity and the social determinants of health. She is engaged in the implementation and evaluation of data and evidence studies, including the social, legal and ethical implications of using these emerging technologies.

She was previously Associate Director of Extramural Science Programs at the National Institute on Minority Health and Health Disparities, NIH and played a key role in advancing trans-NIH and federal strategic efforts. She is the scientific editor of the first authoritative resource manual “The Science of Health Disparities Research” designed to identify research questions, guide collaborative and community engagement efforts to promote equity. in health.

She has published widely on health disparities, evaluation of AI and machine learning technologies, including the integration of health equity, ethical AI and principles of social justice in the AI-ML development lifecycle.


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