Objective
The high degree of tumour (genomic and phenotypic) heterogeneity influences patient’s response to therapy and hampers wide deployment of personalised medicine for cancer treatment. Thus, there is an imperative need for new technologies that can accurately detect tumour heterogeneity, allow for patient stratification and assist clinicians in providing the right diagnosis and treatment for the right patient. PREDICT’s mission is to address this huge unmet need.
Radiomics, a newly emerging field that uses high-throughput extraction of large amounts of features from radiographic images, can boost the field of personalised medicine. The analysis of medical images taken as standard-of-care allows Radiomics to capture tumour heterogeneity and to generate ‘tumour-specific’ signatures in a non-invasive way, without the need of assessing the patient’s genetic profile. Thus, Radiomics, if linked to Big- data and decision support systems (DSS), can be used as diagnostic tool for patient stratification, for prediction of treatment response and for guidance, involving the patient, of clinical decisions in oncology. However, researchers that understand cancer biology, advanced imaging and big data analytics are virtually absent. Even more challenging is to translate the outcomes into actual clinical tools involving the patient.
PREDICT will train 15 highly promising researchers in the emerging field of Radiomics and Big data. These ESRs will be trained to implement the automatic exploitation of large amounts of imaging data to drive decision-making algorithms that will guide diagnosis and treatment of different types of cancer and to develop ‘tumour-specific’ signatures integrated in multifactorial DSS. The ESRs will become experts and innovators in Radiomics, Big Data and DSS, which will allow them to bring unique solutions towards the clinic. PREDICT builds upon a strong consortium with 8 academic and 10 non-academic partners that are all pioneers in their respective field.
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
- natural sciences computer and information sciences data science big data
- medical and health sciences clinical medicine oncology
- medical and health sciences health sciences personalized medicine
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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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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-ETN - European Training Networks
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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.
6200 MD Maastricht
Netherlands
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Participants (9)
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20133 Milan
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4000 LIEGE
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Participation ended
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3015 GD Rotterdam
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69120 Heidelberg
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75654 PARIS
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4000 Liege
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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.
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OX2 0HP Oxford
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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.
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.
OX4 2LL Oxford
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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.
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.
6229 EV MAASTRICHT
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Partners (8)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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6229 EV Maastricht
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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1043NX Amsterdam
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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1210 Bruxelles / Brussel
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2289 DC Rijswijk
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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Munich
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Roma
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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69120 HEIDELBERG
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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69120 Heidelberg
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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.