Eventi

International Workshop - Artificial Intelligence and Cardiovascular Risk Assessment

Fiesole (FI), 16-18 Settembre

Programma

RATIONALE
Atherosclerotic cardiovascular disease (ASCVD) remains the leading global cause of mortality, despite substantial advances in prevention, risk factors control, and pharmacological therapy. Traditional risk prediction models, largely derived from population-based cohorts and based on a limited set of classical well known risk factors, have provided an important framework for estimating cardiovascular risk. However, while useful at the population level, these models fall short when applied to individual patients. They may inadequately capture heterogeneity across age groups, sex, ethnicity, and genetic background, and frequently fail to account for lifetime exposure and dynamic changes in risk, thereby contributing to persistent residual cardiovascular burden.
In recent years, the rapid expansion of large-scale biobanks, electronic health records, advanced imaging modalities, and multi-omics platforms has profoundly transformed the landscape of cardiovascular risk assessment. These resources provide an unprecedented opportunity to move beyond static and simplified risk estimation toward a more comprehensive and dynamic understanding of disease processes. When combined with artificial intelligence (AI) and machine learning approaches, these datasets enable the integration of complex, multidimensional information, capturing interactions between biological, environmental, and behavioural determinants that often are not accessible through conventional models.
Such approaches hold the potential to redefine cardiovascular prevention by enabling more precise, individualized risk stratification, earlier identification of high-risk phenotypes, and more targeted therapeutic interventions. At the same time, they may help to better characterize subclinical disease, refine treatment thresholds, and optimize allocation of healthcare resources.
However, important challenges remain. These include the interpretability and transparency of AI-driven models, the need for rigorous validation across diverse populations and healthcare systems, issues related to data quality and bias, and the practical integration of these tools into clinical workflows. Ethical considerations, including data governance and patient privacy, also represent critical aspects that must be addressed to ensure responsible implementation.
This workshop in Fiesole is designed to address these opportunities and challenges by combining high-level plenary lectures with interactive, hands-on sessions. The program will provide participants with both a strong conceptual framework and practical skills, fostering a multidisciplinary dialogue between cardiology, data science, and public health.
The ultimate aim is to empower clinicians and researchers to critically evaluate, interpret, and apply big data and AI tools in real-world settings, thereby contributing to more effective and sustainable cardiovascular prevention strategies.

FACULTY
Alberico L. Catapano
Ian Graham
John Kelleher
Maryam Kavousi
Brian Ference
Thomas Lüscher

President of the Meeting
Alberico L. Catapano

Scientific Secretariat
Giuseppe Danilo Norata
Associate Professor of Pharmacology
Department of Pharmacological and Biomolecular Sciences
University of Milan
Via G. Balzaretti, 9 - 20133 Milan (Italy)

Co-organized by
Fondazione Internazionale Menarini
Http://www.fondazione-menarini.it

Organizing Secretariat - Provider
Marben S.r.l.
Via Melzi d'Eril, 20 - 20154 Milan (Italy)
Phone: +39 02 349 17 32
Fax: +39 02 349 16 29
Http://www.marben.it