The Evidence for AI in Health (EVAH) initiative is a $60 million joint investment by the Gates Foundation, Novo Nordisk Foundation, and Wellcome Trust to support rigorous, country-led evaluations of AI health tools in low- and middle-income countries. Delivered in partnership with J-PAL and the African Population and Health Research Center, EVAH funds evaluations of AI-enabled clinical decision support tools in primary and community healthcare settings across Sub-Saharan Africa, South Asia, and Southeast Asia. Pathway A supports early-deployment evaluations focusing on usability, workflow integration, and safety for up to $1 million. Pathway B funds randomized controlled trials, economic analyses, and implementation science studies of tools ready for deployment at scale for up to $3 million. The initiative addresses a critical evidence gap about whether AI diagnostic and clinical decision support tools actually improve health outcomes in resource-limited settings.

ARPA-H's ADVOCATE (Agentic AI-EnableD CardioVascular CAre TransfOrmation) program seeks to develop the first FDA-authorized agentic AI technology providing 24/7 specialty cardiovascular care. The program funds three components: a patient-facing clinical AI agent that serves autonomously as a digital member of the care team, a supervisory AI overseer that monitors deployed agents for safety and efficacy, and a clinical workflow integration plan for scalable deployment. ARPA-H will select teams of innovators within six months, with team selections anticipated in June 2026. The program aims to create AI agents capable of continuous patient monitoring, real-time clinical decision support, and autonomous intervention recommendations for cardiovascular disease management.

University of Oxford Institute for Ethics in AI Accelerator Fellowship Programme is sponsored by University of Oxford Institute for Ethics in AI. Flexible, self‑directed research fellowship for individuals across sectors to develop ethical, policy‑relevant AI research under one of core themes (e. g. , AI and Mental Health, AI and Humanity)

Wellcome Discovery Awards provide long-term flexible funding for established researchers and teams pursuing bold, creative research that can deliver significant shifts in understanding of human life, health, and wellbeing. AI and computational approaches to biomedical challenges are explicitly welcome, including machine learning for drug discovery, AI-driven clinical diagnostics, computational genomics, and data science for health equity. The world's second largest private funder of medical research (endowment approximately £14.5 billion), Wellcome supports interdisciplinary teams tackling fundamental health questions using novel methodologies. Discovery Awards are discipline-agnostic and value transformative potential over incremental advances, making them ideal for ambitious AI-health intersection research.

This Digital Europe Programme call funds the deployment of AI-powered image screening tools in medical centres across the European Union for cancer and cardiovascular disease detection. Part of a €63.2 million package of seven Digital Europe calls published on April 21, 2026, this specific topic focuses on integrating validated AI diagnostic tools into clinical workflows to improve early detection rates and screening efficiency. Projects should demonstrate scalable AI-powered diagnostic imaging solutions that can be deployed across multiple medical centres and health systems within the EU. The call supports the European Health Data Space initiative and aligns with the EU's digital health strategy.

Joint NSF/NIH interagency program (NSF 25-542) supporting transformative, high-risk/high-reward advances in AI and advanced data science for biomedical and public health research. Funds interdisciplinary teams developing novel methods to collect, sense, connect, analyze, and interpret health data from individuals, devices, and systems. Six priority themes: fairness and trustworthiness in health AI systems, transformative analytics using AI/ML for biomedical research, multimodal wearable and implantable biomarker sensing systems, cyber-physical systems for closed-loop health interventions, robotics for health outcomes, and biomedical image interpretation combining human perception with computational analysis. All proposals require a mandatory Collaboration Plan demonstrating cross-disciplinary integration.

Innovative Health Initiative Joint Undertaking (IHI JU) is a grant from the European Commission that funds collaborative, cross-sector health research projects spanning pharmaceutical, digital, IT, medical devices, and diagnostics industries. The IHI JU aims to translate health research and innovation into tangible patient benefits by supporting breakthroughs that cross traditional sector boundaries, such as medical device-drug combinations and AI diagnostics. Projects span the full spectrum of care from prevention to diagnosis and treatment, with a focus on unmet public health needs and making Europe's health industries globally competitive. Eligible applicants include health-related industries, SMEs, academic institutions, clinical organizations, patient organizations, and other health research entities from EU member states. Award amounts vary by project call.

AI for Public Health Initiative is sponsored by University of Arizona, Mel and Enid Zuckerman College of Public Health. This initiative seeks to build educational and research capacity in AI and Digital Epidemiology to train a new generation of public health professionals. Funds will support course development, pilot projects, and an endowed chair to lead efforts in using AI for public health challenges, including surveillance and rapid response to emerging threats.

Teaching Future Doctors to Team with AI: A Social Science Approach to Developing and Evaluating Training Methods for Clinical-AI Collaboration Across the ARiSE Network is sponsored by The Macy Foundation. Aims to train doctors to work effectively with AI, enhancing patient safety and adapting to new medical technologies through social science methodologies.

NIH Bridge2AI Stage 2 represents the next phase of the NIH Common Fund Bridge to Artificial Intelligence program building on $130 million invested in Stage 1 to create ethically sourced AI-ready biomedical datasets. Stage 2 shifts focus from data generation to building tools devices and safety frameworks that translate those datasets into clinical and research applications. Two interconnected initiatives are funded: Innovation Funnels supporting teams that use Stage 1 AI-ready datasets to create practical tools including diagnostic algorithms drug discovery platforms and clinical decision support systems that demonstrate measurable health impact and a Network for AI Health Science developing safety measures validation protocols and responsible-use frameworks for AI in health research. The program values interdisciplinary teams combining computational scientists with domain experts in specific disease areas. Stage 2 Requests for Applications are expected by mid-2026. This is distinct from ARPA-H programs which fund specific high-risk clinical AI applications and from AHRQ healthcare AI safety grants which examine existing AI impact on healthcare systems.

NSF SBIR Phase I - Artificial Intelligence is sponsored by National Science Foundation. NSF SBIR funds high-risk AI innovation and R&D. A bike repair shop could only qualify if developing a novel AI technology for commercialization (e. g. , custom AI diagnostic tool for bike repairs), not for adopting existing AI tools.

Digital Health Grants are awarded by the Patrick J. McGovern Foundation (PJMF) to organizations advancing artificial intelligence, data science, and digital health solutions for equitable health care access. PJMF is a philanthropic organization dedicated to AI and data science for a thriving and sustainable future, working across digital health, climate, digital access, and data maturity in the social sector. Past grants have ranged from $100,000 to $750,000. The Foundation supports partnerships with public, private, and social institutions. Notable investments include a $1 million pledge to the Global Fund Digital Health Impact Accelerator to improve digital health infrastructure in five African countries. PJMF does not maintain an open application cycle; interested organizations should contact the Foundation directly.

Discovering the Future of AI Grant Program (AI + Health; AI + Science) is sponsored by University of Pennsylvania (Office of the Vice Provost For Research). This program provides faculty with resources to pursue paradigm-shifting research and education in AI and its applications, including revolutionizing healthcare through AI-driven diagnostics, personalized medicine, computational biology, and applying AI to accelerate discovery.

2025 SSG Awards: SEIRI Seed Grants is a grant from the STEM Education Innovation and Research Institute at Indiana University Indianapolis that funds faculty pilot projects integrating emerging technologies and innovative pedagogical methods into STEM education. In 2025, three projects received a combined $88,466, supporting research on generative AI in psychology curricula, GeoEthics modules, and cross-disciplinary EMR innovation for health AI education. Eligible applicants are faculty members at Indiana University Indianapolis.

Discovering the Future of AI Grant Program is a grant from the Office of the Vice Provost for Research at the University of Pennsylvania that funds faculty pursuing paradigm-shifting research and education in artificial intelligence and its applications. The program supports one-year projects aligned with PennAI's strategic thrusts: AI Foundations, AI and Business, AI and Education, AI and Health, AI and Science, and AI and Society. Proposals from joint teams of two co-principal investigators from different schools are especially encouraged, pairing core AI/ML experts with domain specialists. Eligible applicants are University of Pennsylvania faculty. Successful projects demonstrating broader university impact may be eligible for additional funding in subsequent years.

ARPA-H's PRECISE-AI (Performance and Reliability Evaluation for Continuous Modifications and Useability of Artificial Intelligence) program develops techniques to detect when AI-enabled medical tools used in real-world clinical settings fall out of alignment with their underlying training data and auto-correct these tools to maintain peak performance. The program addresses a critical challenge in healthcare AI deployment: ensuring AI diagnostic and clinical decision support tools remain accurate over time as patient populations, disease patterns, and clinical practices evolve. Performer teams of ML experts, health information specialists, and clinicians will develop capabilities for establishing accurate diagnostic ground truth, monitoring AI performance autonomously, determining root causes of performance degradation, enabling AI models to communicate uncertainty to clinicians, and creating data infrastructure for sharing findings among healthcare stakeholders.

Open Data Micro-Grant Call (Health Equity Award) is a grant from the MICCAI Society that funds the creation of original, publicly available open datasets in medical imaging and clinical AI, with an emphasis on health equity, diversity, and under-represented populations. The program offers two grant tiers: four small grants of $650 and four large grants of $1,200. Eligible costs include data preparation and curation, annotations and quality control, and documentation for public data release; travel costs are not eligible. Eligible applicants are researchers from academia, hospitals, or industry—individuals or teams—with no geographic or career-stage restrictions. Datasets must be released with an open license, and funding is released after paper submission (acceptance is not required). Ethical approval must be obtained prior to application.