Objective
Clinical experts make design decisions on treatments, interventions, or on devices. ICT empowers them with patient-specific simulation models that enable better-informed design decisions. But patient-specific computational medicine is currently cumbersome, slow, and unintuitive; it relies on complex processing by technical experts, and it is hence far from reaching its full potential on clinical design, and scarcely used.
RAINBOW envisions next-generation biomechanics simulation and optimization tools for personalized clinical design that are rapidly setup for a particular patient, have a fast learning curve, are easy-to-use by clinical experts, and do not require intervention by a technical team. Research objectives entail automated processing of patient data; automated setup of representations and parameters, capability to manage variance across patients; robust and accurate simulation as a latent part of design tools; and fast optimization methods that allow intuitive exploration of the design space. Novel computational methods will be created to reach the objective of rapid biomechanics simulation. RAINBOW will apply research solutions for diagnosis, prognosis, monitoring, surgical training, planning, guidance, design of prosthetics, implants, and medical devices, and will address health conditions such as osteoarthritis, scoliosis, hearing impairment, cardiovascular diseases, obesity etc.
RAINBOW has 5 excellent academic participants: UCPH (medical imagine, machine learning), URJC (data-driven modeling), UL (computational mechanics), CARDIFF (model reduction), AAU and one hospital HH (bone modeling) and 8 industries 3Shape (prosthesis), Kitware (imaging), Insimo (surgical simulation), GMV (eHealth), Simpleware (CAD/CAE), inuTech (numerics), Anatascope (Patient specific modeling) and Next-Limit (CFD). This combined expertise will ensure diverse impact and training of highly qualified individuals.
Fields of science (EuroSciVoc)
- natural sciences computer and information sciences computational science
- medical and health sciences clinical medicine cardiology cardiovascular diseases
- natural sciences biological sciences biophysics
- medical and health sciences medical biotechnology implants
- natural sciences computer and information sciences artificial intelligence machine learning
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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers
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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.
MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)
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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) H2020-MSCA-ITN-2017
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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.
1165 KOBENHAVN
Denmark
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Participants (9)
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4365 ESCH-SUR-ALZETTE
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28933 Mostoles
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CF10 3AT CARDIFF
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3400 Hillerod
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1060 KOBENHAVN
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28760 TRES CANTOS MADRID
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RG7 4SA READING BERKSHIRE
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9220 AALBORG
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1060 KOBENHAVN
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Partners (5)
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28002 MADRID
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
69100 VILLEURBANNE
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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67091 Strasbourg
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34960 Montpellier
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90429 Nuremberg
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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.