Fuzzy MLP based expert system for medical diagnosis

Abstract

A fuzzy MLP model, developed by the author, is used as a connectionist expert system for diagnosing hepatobiliary disorders. It can handle uncertainty and/or impreciseness in the input as well as the output. The input to the network is modelled in terms of linguistic pi-sets whose centres and radii along each feature axis are determined from the distribution of the training data. In case of partial inputs, the model is capable of querying the user for the more important feature information, when required. Justification for an inferred decision may be produced in rule form. A comparative study of the performance of the model with other methods is also provided.