Purpose

Innovation in Under-Resourced Settings provides funding to catalyze multi-disciplinary research projects to plan and pilot Artificial Intelligence/Machine Learning (AI/ML) algorithms or tools to address health disparities in cancer, cardiometabolic and mental/behavioral health. The projects must engage healthcare organizations serving patients in Federally Qualified Health Centers (FQHCs) or Community Health Centers from medically under-resourced areas as defined by Health Resources and Services Administration (HRSA) and/or serving a disproportionately high percentage(s) of NIH-designated health disparity populations to design and pilot AI/ML-aided tools, models or interventions.

Participants

Six teams have been awarded a first year of funding to form collaborative, equal partnerships with providers serving FQHC or health disparity populations. The 2024-2025 application cycle drew proposals from private and public institutes of higher education, non-profits, small businesses and for-profit organizations, and a tribal health organization. Most applications (66%) were led by non-academic institutions, demonstrating potential for partnership-building/knowledge transfer.

Regional Distribution of Cohort 1 Awardees

Impact

The program seeks applications that go beyond data-only studies by co-designing and piloting AI/ML interventions in partnership with impacted communities. Funded projects will transfer knowledge and AI/ML capabilities with institutions or communities serving populations that disproportionately experience health disparities and barriers to care.

Program Inquiries

All questions and inquiries regarding this program can be directed to the CDP HelpDesk. Please create a help ticket here: HelpDesk - Submit a Ticket