Multilevel modelling for decision support in hypertrophic cardiomyopathy in the SMASH-HCM project

Authors

• Alpo Olavi Värri Faculty of Medicine and Health Technology, Tampere University, Tampere http://orcid.org/0000-0002-3214-3458
• Mark van Gils Faculty of Medicine and Health Technology, Tampere University, Tampere https://orcid.org/0000-0002-0029-1771
• Jari Hyttinen Faculty of Medicine and Health Technology, Tampere University https://orcid.org/0000-0003-1850-3055

DOI: https://doi.org/10.23996/fjhw.143516

Keywords:

hypertrophic cardiomyopathy, modelling, artificial intelligence, decision support

Abstract

Hypertrophic cardiomyopathy (HCM) is the most common inherited genetic heart disease, and its most feared outcome is a sudden death even in a young otherwise healthy adult. The EU-funded project SMASH-HCM aims at dramatically improving HCM stratification and disease management, both for clinicians and patients. The project combines data from the patients at multiple levels, from genetic and molecular data to in-silico physiological and family history data and creates in-vitro and computational models of the disease at these various levels. A digital twin of the patient will be formed based on these data modelling tasks. Modelling approaches, data-driven artificial intelligence and knowledge existing in literature will complement each other to provide decision support for the clinicians to optimize interventions, and actionable information about the disease status and development will be offered to the patient.