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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social scienceseconomics and businessbusiness and managementinnovation management
- natural sciencescomputer and information sciencesdata sciencebig data
- medical and health sciencesclinical medicineoncology
- medical and health scienceshealth sciencespersonalized medicine
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Programme(s)
Funding Scheme
MSCA-ITN-ETN - European Training NetworksCoordinator
6200 MD Maastricht
Netherlands
See on map
Participants (9)
20133 Milan
See on map
4000 Liege
See on map
Participation ended
3015 GD Rotterdam
See on map
69120 Heidelberg
See on map
75654 Paris
See on map
4000 Liege
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
OX2 0HP Oxford
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
OX4 2LL Oxford
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
6229 EV Maastricht
See on map
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partners (8)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
6229 EV Maastricht
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1043NX Amsterdam
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1210 Bruxelles / Brussel
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
2289 DC Rijswijk
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Munich
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Roma
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
69120 Heidelberg
See on map
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
69120 Heidelberg
See on map