Modeling of the human body using stochastic Petri nets

The advancement of science and medicinal technology both facilitate and necessitate an increase in the understanding of the human body, its subsystems, and their reliabilities. One of the most prominent examples of this is in the possible creation of synthetic organs, which will need benchmarks for their dependability before approval for implantation. While lower-level biological processes have been simulated using traditional reliability modeling approaches, this research extends the body of knowledge by instead taking a top-down approach. In this work, a model of the human body was derived using a Generalized Stochastic Petri Net (GSPN) by exploiting the similarities between the human body and traditional fault-tolerant systems. Although the simulation results proved that more detailed medical statistics are needed prior to implementation, the research does provide a foundational model for future work in this area.