Project description
A framework for responsible generative AI
Machine learning (ML) has a future in the healthcare sector, but limited data setsand privacy regulations constrain progress. Generative AI can produce synthetic data, but trust issues with fairness and privacy hinder its use. With the support of the Marie Skłodowska-Curie Actions programme, the THUNDER project aims to address gaps in trustworthy generative models and machine learning methods for healthcare, particularly around standardised evaluation frameworks and trust issues. Its main goal is to develop a comprehensive framework for responsible generative AI in healthcare, with an emphasis on defining evaluation metrics, creating knowledge-guided generative models, and designing interpretable learning models. The project will particularly target sepsis, a global health priority designated by the World Health Organization (WHO).
Objective
Machine learning (ML) offers transformative opportunities for healthcare, with applications ranging from precision medicine to operational optimization. However, progress is constrained by limited access to diverse, high-quality datasets, exacerbated by fragmentation, data scarcity, and stringent privacy regulations. Traditional data augmentation methods fail to fully capture the complexity and heterogeneity of healthcare data. Generative AI, particularly large language models (LLMs), offers a promising alternative by synthesizing realistic datasets while addressing data scarcity. Yet, their adoption in healthcare is hindered by critical concerns about trustworthiness, including semantic validity, fairness, bias mitigation, fidelity, privacy preservation, and real-world utility. This research identifies key gaps in developing trustworthy generative models and ML methods for healthcare. These include the absence of standardized synthetic data evaluation frameworks, trust deficits in healthcare generative models, resource intensiveness, and design-induced opaqueness. The overall objective of the THUNDER project is to forge a comprehensive framework for trustworthy and responsible generative AI in healthcare. This will be achieved by defining (i) standardized evaluation metrics, (ii) developing advanced knowledge-guided generative models, and (iii) creating a fully frugal-by-design and interpretable-by-design learning models. These efforts, driven by interdisciplinary and intersectoral mobility and knowledge exchange, will establish a new paradigm for AI-driven healthcare. We will target Sepsis as a global health priority identified by the World Health Organization (WHO).
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.
This project's classification has been human-validated.
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.
This project's classification has been human-validated.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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-TMA-MSCA-SE - HORIZON TMA MSCA Staff Exchanges
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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) HORIZON-MSCA-2024-SE-01
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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.
78035 VERSAILLES
France
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.