The AIM-AHEAD Federated Data Network seeks to empower biomedical research by establishing a decentralized, data network that respects data privacy and sovereignty. With federated technology, participating sites keep data locally, opting in to securely share only aggregate results for collaborative analyses. This infrastructure, supported by AIM-AHEAD, facilitates the study of sensitive health topics, advances community health, and promotes an AI/ML research environment aligned with AIM-AHEAD objectives.
AIM-AHEAD Federated Network
Goals of Federated Network
Strengthen Data Ecosystems
Integrate with AIM-AHEAD Cores
Federated Network
Program Awardees
The four awarded sites with local patient-level data for the Federated Network Program share a unified commitment to support communities that lack the resources or capacity to benefit from advancements in AI/ML applications in healthcare. By equipping these institutions with AI/ML capabilities, the AIM-AHEAD program empowers them to generate insights and develop solutions tailored to the specific health challenges faced by their populations.
Geographical Distribution of Awardees by Institution
Impact
The Federated Network Program will set up the awarded four participating sites to drive transformative outcomes through tailored protocols for data curation and sharing. These protocols will be customized to each institution’s unique context, drawing on insights gained throughout the process. Collaborating closely with core team members, the awarded sites will assess their capacity to run AI/ML models locally and share resulting outputs.
As part of the second-year objectives, the sites are expected to compile and share aggregated data to address pressing research questions, enabling the broader research team to perform federated analyses. This coordinated approach aims to enhance community-based capabilities and foster sustainable advancements in health through AI/ML.
Program Inquiries
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Program Directors
Paul Avillach, MD, PhD; Griffin Weber, MD, PhD; Usha Sambamoorthi, PhD; Gabriel Brat, MD, MPH; Tianxi Cai, PhD;