Project description
Bridging the AI gap in global healthcare
In many low- and middle-income countries, the promise of AI in healthcare is hindered by a persistent digital divide. Challenges such as data privacy concerns, unreliable infrastructure and complex legal frameworks make it difficult to fully harness the power of big data and medical AI. The ERC-funded AIFIX project will address this gap with an ambitious solution: a federated learning platform that enables local AI training without data transfers or privacy risks. Designed to thrive even in low-bandwidth settings, AIFIX will be tested through a global obstetric imaging study across Europe, Africa and Asia. By bringing together clinicians, data scientists and local stakeholders, AIFIX will pave the way for more inclusive and equitable AI in healthcare.
Objective
"The AIFIX project is a transformative initiative aiming to bridge the ""healthcare AI divide"" by developing an adaptive federated intelligence platform to securely integrate medical imaging data across diverse environments. It specifically targets the inclusion of low- and middle-income countries (LMICs), where limited data availability, privacy concerns, and inadequate legal frameworks have traditionally hindered AI innovation in healthcare.
AIFIX will deliver an adaptive federated learning platform to enable the local training of AI models without the need to transfer raw data, ensuring privacy and compliance with local data protection laws. The platform will be optimised to operate across a variety of computational resource and internet connections, ensuring efficient and stable performance across diverse data centres.
The feasibility of this approach will be demonstrated through an inter-continental obstetric imaging study involving diverse sites across Europe, Africa and Asia. From the outset, AIFIX will involve a wide range of stakeholders including healthcare professionals, AI innovators, data managers, and legal experts to ensure the platform meets diverse needs and overcomes potential adoption barriers.
Finally, AIFIX will develop a sustainable business model based on detailed market analysis and financial planning. This model will explore various revenue streams such as licensing, subscriptions, and data monetisation, aiming to attract healthcare institutions and AI innovation organisations. The project will also explore federated IP management strategies to protect and share innovations equitably among all contributors.
The AIFIX project will represent a significant leap towards equitable AI innovation and utilisation in healthcare, promising to deliver substantial clinical, economic, and societal benefits across the globe."
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.
- social sciences economics and business business and management innovation management
- social sciences law
- natural sciences computer and information sciences artificial intelligence computational intelligence
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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-2024-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.