An Automated Cardiac Constitutive Modelling Framework with Evolutionary Strain Energy Functions

Abstract Heart disease is the leading cause of mortality worldwide. Many cardiac diseases are associated with altered elastic energy relations heart tissue. However, strain functions describing these characteristics limited since they were designed manually for highly specific experimental setups. In this study, we develop CHESRA (Cardiac Hyperelastic Evolutionary Symbolic Regression Algorithm), an automated constitutive modelling framework, to derive directly from data. Our results indicate that finds reproduce mechanical tissue properties data whilst controlling function complexity. novel approach has potential find strain-energy fit various sets and may contribute automatically building mathematical models understand clinical observations diseases.