Using Knowledge and Rule Induction Methods for Enhancing Clinical Diagnosis: Success Stories

Abstract

The economic and social benefits of accurately predicting medical outcomes are very high. As a result, the problem of improving predictive models has attracted many researchers. Over the past few years there has been great interest in the use of advance knowledge discover techniques to mimic human functions. Research shows that such techniques can be applied in healthcare environments where an automated process must improve its performance based on previous data, adapt to changes and deal with uncertain and incomplete medical knowledge. The underlying purpose of this paper is to illustrate the utility of combining multi agent approach and hybrid machine learning and data mining techniques for producing predictive classifiers in clinical settings.