Building a Knowledge Base of an Expert System for Personalized Stroke Risk Prognosis

Authors present an expert system based on a model with operators that characterize various states of chronic cerebral ischemia. Risk factors (or predictors) that can affect the health, are considered operators in the model. The system of interactions between arguments and counterarguments measured by expert assessments characterizes the changes in the state of the body. Predictors are arguments and protectors are counterarguments. The production rules of the knowledge base are formed on the basis of attribute combinatorics, where predictors and protectors are regarded as attributes. The expert system, which includes multiple combinations of predictors and protectors, will make it possible to form personalized prognostic hypotheses for patients at different periods of time with regard to the changes in risk factors. The coefficients may be re-evaluated if required when new knowledge emerges. Expanding the knowledge base is possible by creating rules that include new factors.