Diagnosis support using fuzzy cognitive maps combined with genetic algorithms

A new hybrid modeling methodology to support medical diagnosis decisions is developed here. It extends previous work on competitive fuzzy cognitive maps for medical diagnosis support systems by complementing them with genetic algorithms methods for concept interaction. The synergy of these methodologies is accomplished by a new proposed algorithm that leads to more dependable advanced medical diagnosis support systems that are suitable to handle situations where the decisions are not clearly distinct. The technique developed here is applied successfully to model and test a differential diagnosis problem from the speech pathology area for the diagnosis of language impairments.