Project description
Computational biomarkers for myocardial infarction risk
Myocardial infarction (MI) is a major global cause of death but current prediction tools for ischaemic and bleeding risks after therapy suffer from limited precision. Funded by the European Research Council, the ORACLE project aims to improve risk prediction by utilising multidimensional data from wearable devices, biomarkers, and non-invasive imaging. The idea is to identify novel computational biomarkers for risk using AI to analyse data from a large cohort of MI patients. The project is expected to generate clinically guided AI algorithms and integrate them into practice for informed treatment decisions.
Objective
Myocardial infarction (MI) is a leading cause of death worldwide. After MI, long-term antithrombotic therapy is crucial to prevent recurrent events, but increases bleeding, that also impacts morbidity and mortality. Giving these competing risks prediction tools to forecast ischemic and bleeding are of paramount importance to inform clinical decisions, but their current precision is limited. Improve events prediction, by discovering novel and innovative markers of risk would have a tremendous impact on therapeutic decisions and patients outcome. I hypothesize that using innovative multidimensional information from wearable devices, biomarkers, behavioral patterns and non-invasive imaging, integrated through artificial intelligence computation, we may discover novel computational biomarkers of risk and improve current standards of risk prediction. In this project, I will enroll a large cohort of MI patients, whereby prospective collection of consolidated and innovative potential risk predictors will take place, in order to generate a comprehensive and multidimensional dataset. I will collect data from state-of-the-art non-invasive imaging, blood biomarkers, wearable medical devices of continuous heart electrical activity, sweat, mobility and behavioral patterns to create a large physiological time series allowing patients deep phenotyping. We will therefore analyze data leveraging artificial intelligence computation to find relevant associations with clinical outcomes, and compare new algorithms with current risk prediction tools. This research will increase our knowledge on bleeding and ischemic risk factors, enabling enhanced capability predictions models. In the near future, we hypothesize that our clinically-guided Artificial Intelligence algorithm might be integrated in clinical practice, helping clinicians to inform treatment decisions, patients to better understand their risk profile, finally setting a common ground for shared patient/physician decisions.
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.
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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.1.1 - European Research Council (ERC)
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-ERC - HORIZON ERC Grants
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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) ERC-2023-STG
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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.
29590 MALAGA
Spain
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.