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PRIMED-AI: Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (UG3/UH3 Clinical Trial Optional)

National Institutes of Health · Opportunity RFA-RM-27-012

Who can apply

• State governments
• County governments
• City or township governments
• Special district governments
• Independent school districts
• Public and State institutions of higher education
• Native American tribal governments (Federally recognized)
• Public housing authorities
• Native American tribal organizations (other)
• Nonprofits with 501(c)(3), other than higher education
• Nonprofits without 501(c)(3)
• Private institutions of higher education
• For-profit organizations other than small businesses
• Small businesses
• Others

Refer to Section III. Eligibility Information in the NOFO for additional information on eligibility.Foreign Organizations/International Collaborations:Non-domestic (non-U.S.) Entities (Foreign Organizations) are eligible to apply.Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply.Foreign components, as defined in the NIH Grants Policy Statement, are allowed.

About this opportunity

The overarching goal of this notice of funding opportunity (NOFO) and its companion opportunities is to establish the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program to support development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools. PRIMED-AI CDS tools are based on the integration of clinical imaging with other types of multimodal health data to enhance care for patients with a wide range of health conditions. The PRIMED-AI Program seeks to catalyze the adoption of AI-based CDS tools into clinical workflows to enable novel personalized medicine strategies that address significant health challenges. The purpose of this Notice of Funding Opportunity (NOFO) is to catalyze the development and testing of Artificial Intelligence (AI)-enabled, image-centered, multimodal Clinical Decision Support (CDS) tools, developed in pursuance as Software as a Medical Device (SaMD). These projects are expected to have high potential for demonstrable, positive impact on patient outcomes and/or healthcare processes.

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