Project description
Tackling brain disorders with AI
Medical imaging powered by AI is changing healthcare. However, most AI systems still provide only static snapshots instead of tracking how diseases progress over time. Supported by the Marie Skłodowska-Curie Actions programme, the BRIDGE-AI project will train doctoral candidates to create AI tools that monitor and predict brain disorders throughout life. Candidates will work with experts from universities, hospitals, scanner manufacturers, and AI companies, connecting clinical needs with research and practical applications. With access to large neuroimaging datasets and interdisciplinary support, BRIDGE-AI will develop imaging AI that tracks changes over time, improves treatment predictions, and encourages open-source solutions. This will ensure a significant clinical impact and the wide dissemination of new ideas.
Objective
BRIDGE-AI will train a new generation of innovative and entrepreneurial-oriented doctoral candidates (DCs) to move the state-of-the-art away from the snapshot interpretation of medical images by AI to a longitudinal follow-up and prediction of disease progression, covering a wide range of brain disorders across the entire lifespan. In an innovative departure of prevalent training models, each of BRIDGE-AI's DCs will be co-supervised by internationally leading experts from university research in biomedical image computing, world-renowned research hospitals, leading scanner manufacturers (Siemens, Philips) and medical imaging AI companies (incl. Bayer). Through this unique network, BRIDGE-AI will complete the entire circle from clinical needs to image acquisition, academic AI solution proposal, and commercial product for tracking disease progression and predicting treatment response in individual patients. Each of BRIDGE-AI's DCs will have a dedicated multidisciplinary and multisectoral thesis board, receiving input from industry, academia, and hospitals, and having access to large collections of clinical neuroimaging data, facilitating the evaluation of the true clinical relevance and impact of the proposed disease monitoring tools. Wide dissemination of the obtained methodological advances will be ensured by adopting a strong network-wide focus on open-source software.
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.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences software
- engineering and technology medical engineering diagnostic imaging
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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)
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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-DN - HORIZON TMA MSCA Doctoral Networks
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-DN-01
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02150 Espoo
Finland
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Participants (4)
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3012 Leuven
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5612 AE Eindhoven
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53127 Bonn
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1090 Wien
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Partners (13)
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1015 LAUSANNE
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5684 PC Best
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3584 CX Utrecht
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3012 Bern
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4031 Basel
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02129 Charlestown
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1011 Lausanne
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1348 LOUVAIN LA NEUVE
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53127 Bonn
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6312 ZURICH
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1050 Wien
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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53113 Bonn
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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13353 Berlin
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