Development of an AI-based diagnostic tool for Personalized patient’s risk stratification in CARdiovascular Disease- PAI-CARDIA The P-CARDIA project aims to develop an innovative diagnostic tool based on Artificial Intelligence models for personalized risk stratification in CVD patients using cutting-edge technologies and advanced imaging methods. The risk assessment algorithm will be fed with multidisciplinary data: haematological […]
The ELISAH project aims to reduce the burden of breast cancer inEurope by targeting modifiable risk factors such as pollution, nutrition, physical inactivity, alcohol, tobacco, and the built environment. Since 90–95% of breast cancer cases are linkedto lifestyle and environmental conditions rather than genetics, ELISAH adopts a holistic, multi- directional approach that combines structural interventions with individual health promotion, while addressing the
Development of advanced portable biophotonic system for the personalized spectroscopic distrimination of cancer margins/tissues Co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code:Τ2EDK-01223). Participants: School of Applied Mathematics and Physical Sciences of
Development of a novel and usable web-based platform for cardiovascular risk estimation based on Artificial Intelligence (EUCARDIA), NSRF 2014–2020 (European Social Fund – ESF / European Regional Development Fund – ERDF), ΓΓ1CL-0058514 & ΓΓ2CL-0353180 Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, with a serious social and economic impact. The biggest challenge in
