CBC Talk onMultivariate metamodelling for more efficient model development and validation - March 4, 2015
Total number of participants: 7
Total number of guests outside of CBC: 0
Number of different nationalities represented: 3
Total number of speakers: 1
Total number of talks: 1
Multivariate metamodelling for more efficient model development and validation
Modelling in biology and physiology is increasingly realising its potential to provide a deeper understanding of biological function, guide the development of new intervention strategies and inform treatment optimisation in personalised medicine. However, the development and validation of large, multi-scale models remain hampered by several significant challenges - such as high complexity and computational demand, ill-posed inverse problem of parameter fitting, difficulties in selecting the most informative metrics to measure in order to fit model parameters and a limited ability to effectively bridge between time and space scales - which limit the clinical applicability of models and their adaptation to fit new contexts. This talk will show how multivariate metamodelling, i.e.
statistical modelling of the relationships between model input parameters and phenotypic outputs, has the potential to allow us to overcome a number of these challenges.
Center for Biomedical Computing (CBC) aims to develop and apply novel simulation technologies to reach new understanding of complex physical processes affecting human health. We target selected medical problems where insight from mathematical modeling can contribute to changing clinical practice.