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Personalized Phenotype of Atrial Fibrillation for Accurate Treatment

Objective

Atrial Fibrillation (AF) is the most common cardiac arrhythmia with an EU health cost of 13.5 billion annually. Despite the worsening that this cardiac arrhythmia provokes on the life quality of more than 6 million Europeans, AF therapies are suboptimal: success rate is below 60% including pharmacological and surgical approaches. AF is a multifactorial and progressive disease with high patient heterogeneity and therefore “the same treatment for all” is not optimal.
GUIDE-AF addresses this challenge by a multi-sectorial and multidisciplinary research and training program in novel technologies for the individualization of the AF phenotype with the aim to increase treatments’ efficiency. GUIDE-AF will integrate data and knowledge from anatomical, biological, biomechanical and electrophysiological approaches to generate an accurate description of the patient-specific disease phenotype. The effect of the different AF treatments will be described and quantified for each AF phenotype in order to provide the best therapy choice.
GUIDE-AF project will build a machine learning-based decision support system able to characterize the disease state and progression and able to predict the outcome of therapies. This algorithm will be based on technologies co-developed and validated by the candidate and the host and beneficiary research groups. GUIDE-AF will count with experts in cardiac arrhythmia management, AF characterization through image and signal analysis, basic and clinical research, as well as access to one of the largest AF patient database.
GUIDE-AF will have an eminently multidisciplinary and clinical approach and will focus on providing a feasible and implantable solution for increasing the therapy success and reducing human and health system costs. This proposal includes intensive training for the candidate in new advanced technologies for cardiac characterization and disease profiling, as well as knowledge transfer from and to the host and beneficiary institutions.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

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(opens in new window) H2020-MSCA-IF-2020

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Coordinator

UNIVERSITAT DE VALENCIA
Net EU contribution

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.

€ 204 415,68
Address
AVENIDA BLASCO IBANEZ 13
46010 Valencia
Spain

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Region
Este Comunitat Valenciana Valencia/València
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 204 415,68

Partners (1)

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