Modeling of Parkinson's Disease Using Fuzzy Cognitive Maps and Non-Linear Hebbian Learning

Abstract

Parkinson's disease is a chronic, progressive, age-related, neurodegenerative disorder that affects a large population around the world. A mathematical model for Parkinson's disease is presented using Fuzzy Cognitive Maps (FCMs). Basic theories of FCMs are reviewed and presented. Decision Support Systems (DSS) for medical problems are reviewed. Non-linear Hebbian learning techniques are considered in studying Medical problems and a generic algorithm is presented. The proposed method used the knowledge of a number of experts and simulations were performed obtaining interesting results. Comparisons of the results of the proposed method, both by making use and not making use of learning algorithms, are presented. Some interesting future research directions are mentioned.