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End user-driven application of Generative Artificial Intelligence models in healthcare (GenAI4EU)

This Horizon Europe funding call focuses on advancing the application of trustworthy Generative Artificial Intelligence (GenAI) models in healthcare. The initiative supports research aimed at enabling equal access to innovative, high-quality healthcare through user-centric AI solutions. Key objectives include the development of robust GenAI-based virtual assistants to enhance clinical decision-making, improve patient outcomes, and increase the efficiency of healthcare systems. Projects should address biases, ethical implications, and trustworthiness, incorporating diverse health data and stakeholder engagement, including healthcare professionals and patients. Proposals should demonstrate clinical utility and cost-effectiveness, adopt open-source principles where feasible, and consider regulatory strategies for sustainable implementation. Cross-disciplinary approaches, adherence to FAIR data principles, and collaboration with existing European data infrastructures are strongly encouraged.

Opening: 22-05-2025
Deadline(s): 18-09-2025

Data provided by Kooperationsstelle Wissenschaft

This funding opportunity represents a pre-agreed draft that has not yet been officially approved by the European Commission. The final, approved version is expected to be published in the first quarter of 2025. This draft is provided for informational purposes and may be used to preliminarily form consortia and develop project ideas, but it is offered without any guarantees or warranties.

Expected Outcome

- Healthcare professionals gain access to efficient, trustworthy AI tools for personalized care.
- Enhanced public trust and cross-country applicability of AI healthcare tools.
- Patients experience improved outcomes, personalized care, and better communication with healthcare providers.
- Healthcare systems benefit from cost-effective, high-quality outcomes enabled by GenAI-based solutions.

Scope

- Develop trustworthy Generative AI-based virtual assistant solutions leveraging multimodal health data.
- Address challenges such as biases, ethical considerations, and trustworthiness in AI applications.
- Demonstrate clinical utility and cost-effectiveness through healthcare use cases.
- Engage diverse stakeholders, including healthcare professionals and patients, in solution development.
- Promote methodologies for continuous assessment of AI tools’ performance and ethical compliance.

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