Examination of the Parameter Space of a Computational Model of Acute Ischaemic Stroke Using Rough Sets

Abstract

Complex diseases such as stroke and cancer involve a wide range of biological parameters with respect to the systems involved and disease progression. Computational models of such diseases have led to new insights into the mechanism of action which have resulted in the development of novel therapeutic intervention strategies. Such models are generally quite complex because they incorporate a wide range of relevant biological variables and parameters. In this paper, we examine a biologically realistic computational model of acute ischaemic stroke with respect to the variable and parameter space using rough sets. The aim of this investigation was to extract a set(s) of variables and relevant parameters that predict in a qualitative fashion the final extent of tissue damage caused by a "typical" ischameic stroke.