Detection of the Onset of Diabetes Mellitus by Bayesian Classifier Based Medical Expert System

Abstract

Expert systems play an important role in medical diagnosis research. Researches are still being conducted for building expert systems capable of diagnosing different diseases. Diabetes mellitus is one of the diseases that have gained attention in the past years. Patients are usually unaware of having this disease and are finally diagnosed with diabetes after several years from onset. Since diabetes can be controlled, it is much desirable to harness it at the onset. Therefore, the prediction of onset of diseases like diabetes has been the point of interest for the researchers. Researchers are continuously trying to formulate an inference engine, a part of an expert system, in order to predict the disease at the beginning. In this paper, we present a Bayesian classification approach to identify the onset of diabetes mellitus in patients using a well-known data set as the sample. We have found an intriguing result with more than 87% accuracy.