Objective
Valvular Heart Disease currently affects 2.5% of the population, but is overwhelmingly a disease of the elderly and consequently on the rise. It is dominated by two conditions, Aortic Stenosis and Mitral Regurgitation, both of which are associated with significant morbidity and mortality, yet which pose a truly demanding challenge for treatment optimisation. By combining multiple complex modelling components developed in recent EC-funded research projects, a comprehensive, clinically-compliant decision-support system will be developed to meet this challenge, by quantifying individualised disease severity and patient impairment, predicting disease progression, ranking the effectiveness of alternative candidate procedures, and optimising the patient-specific intervention plan. This algorithmically-driven process will dramatically improve outcomes and consistency across Europe in this fast-growing patient group, maximising individual, societal and economic outcomes.
Fields of science
- medical and health sciencesbasic medicineanatomy and morphology
- social sciencessociologydemographymortality
- natural scienceschemical sciencesinorganic chemistryalkaline earth metals
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencesmathematicsapplied mathematicsnumerical analysis
Programme(s)
Topic(s)
Funding Scheme
RIA - Research and Innovation action
Coordinator
S10 2TN Sheffield
United Kingdom
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Participants (12)
78180 Montigny Le Bretonneux
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5623EJ Eindhoven
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30-059 Krakow
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13353 Berlin
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35065 Rennes Cedex
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13125 Berlin
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5656 AG Eindhoven
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22335 Hamburg
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S10 2SB Sheffield
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35000 Rennes
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
5612 AE Eindhoven
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BS8 1QU Bristol
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