Modeling the human circulatory system using system dynamics: possibilities, benefits, and practical applications

Abstract

System dynamics is a robust methodology for understanding the behavior of complex systems over time. Employing feedback loops, stocks, flows, and time delays provides a framework for simulating and analyzing dynamic systems. Applying system dynamics to the human circulatory system offers numerous possibilities, benefits, and practical applications that can significantly enhance our understanding and management of cardiovascular health. This article presents experimental results of modeling myocardial infarction conditions based on system dynamics with a six-compartment model built using NetLogo integrated development environment, including BehaviorSpace as part of this environment for simulations. For the analysis of the results, specialized packages in R programming language, Python environment, and Wolfram Mathematica were used. The results show promising fidelity when compared with data described in the literature, as well as real-time patient data.