Objective
Conversational assistants powered by generative AI have great potential to improve healthcare in low-Conversational assistants powered by generative AI have great potential to improve healthcare in low-resource settings, where shortages of specialists limit access to quality imaging diagnostics. By combining image analysis with natural-language interaction, these systems can transform complex AI outputs into intuitive, user-friendly guidance, enabling minimally trained healthcare workers, such as nurses and technicians, to acquire images, interpret results, and generate structured reports within routine clinical workflows.
However, current generative AI technologies have been mostly developed in high-income countries, and are largely designed for well-resourced clinical centres. Their deployment in low-resource settings is constrained by high computational demands, reliance on cloud connectivity, limited support for local languages, and poor adaptation to local clinical workflows.
GenAIMIX will address these challenges by introducing a new class of context-aware generative AI assistants tailored to low-resource environments. The project will develop edge-deployable vision–language models capable of running fully offline on low-power devices, delivering real-time guidance during imaging acquisition by non-expert users. The system will integrate clinical reasoning aligned with local protocols and support multilingual interaction, including English and Swahili, ensuring seamless integration into frontline care.
The proposed solution will be deployed and evaluated in three rural maternal health clinics in Kenya, assessing its impact on obstetric ultrasound acquisition quality, clinical interpretation, and usability for minimally trained healthcare workers, such as midwives and nurses. In parallel, GenAIMIX will define exploitation strategies to enable future deployment across Africa and beyond, paving the way for more equitable access to diagnostic imaging worldwide.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-POC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
08007 Barcelona
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.