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Machine Learning Artificial Intelligence Early Detection Stroke Atrial Fibrillation

Sector: Hospital • Location: France, United Kingdom, Germany, Netherlands, Greece, Spain, United States, Canada

Source: EU Funding & Tenders Portal

Project
Ongoing

Atrial fibrillation (AF) and stroke are major health care problems in Europe. They are most often the clinical expression of atrial cardiomyopathy, which is under-recognised due to the lack of specific diagnostic tools. Multidisciplinary research and stratified approaches are urgently needed to prevent, diagnose, and treat AF and stroke and preempt the AF-related threat to healthy ageing in Europe

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The project “Machine Learning Artificial Intelligence Early Detection Stroke Atrial Fibrillation” is an infrastructure initiative in the Hospital sector, located in France, United Kingdom, Germany, Netherlands, Greece, Spain, United States, Canada. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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Description

Description

Atrial fibrillation (AF) and stroke are major health care problems in Europe. They are most often the clinical expression of atrial cardiomyopathy, which is under-recognised due to the lack of specific diagnostic tools. Multidisciplinary research and stratified approaches are urgently needed to prevent, diagnose, and treat AF and stroke and preempt the AF-related threat to healthy ageing in Europe. MAESTRIA is a European consortium of 18 clinicians, scientists and Pharma industrials who are at the forefront of research and medical care of AF and stroke patients. It will create multi-parametric digital tools based on a new generation of biomarkers that integrate artificial intelligence (AI) processing and big data from cutting edge imaging, electrocardiography and omics technologies. It will develop novel biomarkers, diagnostic tools and personalized therapies for atrial cardiomyopathy. Digital Twin technologies, a rich data integrator combining biophysics and AI will be used to generate virtual twins of the human atria using patient-specific data. Unique experimental large-animal models, ongoing patient cohorts and a prospective MAESTRIA cohort of patients will provide rigorous validation for new biomarkers and newly developed tools. A dedicated core lab will collect and homogenize clinical data. MAESTRIA will be organized as a user-centered platform, easily accessible via clinical parameters routinely used in European hospitals. A Scientific Advisory Board comprising potential clinician users will help MAESTRIA meet clinical and market needs. Dissemination and visibility of the MAESTRIA consortium mission will benefit from participation of the German Competence Network on Atrial Fibrillation (AFNET), and support from the European Society of Cardiology, clinicians, scientists, and other professional societies. MAESTRIA will be ready to tackle the major challenges of data integration and personalized medicine focused on atrial cardiomyopathy, AF and stroke.

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High

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100%

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