The interest in AI/ML from underrepresented communities is wide-ranging, and the potential applications of AI/ML in the field of health disparities research is also broad. Through engagement with the consortium members, the A-CC will prioritize and determine the AI/ML and health disparities research use cases that will be enabled by the AIM-AHEAD program. This will be done, for example, through stakeholder engagement, training and education opportunities, and pilot Page 7 of 32 projects with the consortium members. The resulting use cases will be used to drive the design of the data and computing infrastructure and associated data governance models and training offerings for the AIM-AHEAD program.

Research use cases are anticipated to involve linking and preparing multiple sources and types of research data to form an inclusive basis for AI / ML that will illuminate strategies and approaches to ameliorate health disparity.This may include facilitating the extraction and transformation of data from electronic health records(EHR) for research use and consideration of social determinants of health as crucial contributors to health.This is an opportunity to foster the adoption of standardized data structure such as Fast Healthcare interoperability Resources(FHIR®) in accessing and exchanging data from EHR.

In this award period, this core focuses on assessment and planning as well as seizing early opportunities to build capabilities that are either necessary for training and/ or necessary to address the emerging priority use cases.