title: A combined Fuzzy Cognitive Map and decision trees model for medical decision making.
abstract: Fuzzy Cognitive Maps (FCMs) are an efficient modeling method providing flexibility on the simulated system's design. They consist of nodes-concepts and weighted edges that connect the nodes and represent the cause and effect relationships among them. The performance of FCMs is dependent on the initial weight setting and architecture. This shortcoming can be alleviated and the FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This research proposes a successful attempt to combine fuzzy cognitive maps with decision tree generators. A combined Decision Tree-Fuzzy Cognitive Map (DT-FCM) model is proposed when different types of input data are available and the behavior of this model is studied. In this research work, we introduce a new hybrid modeling methodology for decision making tasks and we implement the proposed methodology at a medical problem.
authors.affiliation: Lab. for Autom. & Robotics, Patras Univ., Patras, Greece. epapageo@ee.upatras.gr
authors.forename: Elpiniki
authors.initials: E
authors.lastname: Papageorgiou
authors.forename: Chrysostomos
authors.initials: C
authors.lastname: Stylios
authors.forename: Peter
authors.initials: P
authors.lastname: Groumpos
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003657:Decision Making; D003661:Decision Support Techniques; D003663:Decision Trees; D017143:Fuzzy Logic; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009716:Numerical Analysis, Computer-Assisted; D017063:Outcome Assessment, Health Care; D010363:Pattern Recognition, Automated; D011340:Problem Solving