Summary
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.
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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101024440 |
| Total budget - Public funding: | 204 415,68 Euro - 204 415,00 Euro |
Cordis data
Original description
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.
Status
TERMINATEDCall topic
MSCA-IF-2020Update Date
28-04-2024
Images
No images available.
Geographical location(s)
Structured mapping
