Frans van de Vosse's KTH Solid Mechanics KEYNOTE seminar "Computational Cardiovascular Biomechanics: model predictive decision support and how AI sneaks into it"

Frans van de Vosse March 13 2025.pdf (pdf 161 kB)

Abstract. Given cardiovascular applications, this presentation introduces the digital twin technology concept in the context of model predictive clinical decision support and in-silico clinical trials. The importance and potentials of computational mechanistic models as well as data driven models, and their possible integration in hybrid models will be illustrated using distinctive use cases. The application areas include decision support for treatment and management of patients with, among other things, coronary artery disease, high risk of arrythmia, heart valve disease, and aortic aneurysms as well as decision support in pre-and neonatal care. In addition, the role of evolving AI approaches including generative AI to develop and facilitate reduced order and surrogate (reduced order) models, data augmentation, synthetic patient generation, sensitivity analysis and uncertainty quantification will be addressed. The importance of data quality (by certification) will be discussed.