Project description
A quicker way to diagnose heart attacks
Cardiovascular disease (CVD) is the biggest global cause of death. According to the World Health Organization, there will be 25 million deaths from CVD every year by 2020. An echocardiogram is the most common imaging tool to assess cardiac function. The problem is it takes over 30 minutes to perform and longer for results to be generated and reported. The EU-funded MARCIUS project aims to provide cardiologists a faster diagnostic tool. It will use machine learning to develop a neural network to map inputs to outputs, and intelligent algorithms to provide automatic interpretation of regional cardiac contraction patterns and myocardial image texture.
Objective
Cardiovascular diseases (CVD) are the number one cause of death in EU. Echocardiography is the most important imaging tool to assess cardiac function, since it is real time, cost effective and can be performed without discomfort and harmful radiation. A typical cardiac ultrasound examination takes 30-40 min, with image analysis and reporting doubling this time. Thus, cardiologists are now calling for a step change in diagnostic speed and accuracy to allow significant improvements for the care of CVD patients. We propose to develop intelligent algorithms to provide diagnostic support by automatic interpretation of regional cardiac contraction patterns and myocardial image texture. MARCIUS will leverage recent progress in machine learning to train a neural network to recognize unique disease states using a large database of patient data with known pathophysiology and outcome augmented with virtual patient data obtained using a well-validated mathematical model of the heart and circulatory system in combination with a beyond the state-of-the-art ultrasound simulation tool. The resulting diagnostic algorithm will be validated clinically. MARCIUS will take on research activities with high added value, both clinically for patients suffering from cardiac diseases, commercially for the industrial beneficiary and societally with reducing healthcare costs. The long-term and high-risk aspect of these activities makes them unsuited for execution within a normal product development context. Through training and knowledge development in a focused research project built on a unique combination of state-of-the-art technologies, MARCIUS will provide Europe with researchers trained with the cross-disciplinary understanding and skills necessary to develop enabling technologies in an industrial and clinical setting. The longer-term outcome of the project is new products, which will benefit patients across Europe directly by advancing the state of care within cardiology.
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.
- medical and health sciences basic medicine physiology pathophysiology
- medical and health sciences clinical medicine cardiology cardiovascular diseases
- natural sciences computer and information sciences software software applications simulation software
- natural sciences physical sciences acoustics ultrasound
- natural sciences mathematics applied mathematics mathematical model
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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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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-2019
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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.
3191 Horten
Norway
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.