Purpose

Innovation in Under-Resourced Settings (CDP - Year 3) provides funding to catalyze multi-disciplinary research projects to plan and pilot Artificial Intelligence/Machine Learning (AI/ML) algorithms or tools to address health inconsistencies 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 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 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 Awardees by Hub - Year 3

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 healthcare challenges.

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