Knowledge discovery in medical datasets using a Fuzzy Logic rule based classifier

In the healthcare sector quality demands are rising for designing expert systems for medical diagnosis. At the same time growing capture of biological, clinical, administrative data and integration of distributed and heterogeneous databases create a completely new base for medical quality and cost management. Against this background we applied intelligent data mining methods for analyzing medical repositories. This paper thus assess the role of the data mining techniques namely Fuzzy Logic rule based classifier in the diagnosis of severity of appendicitis in patients presenting with right iliac fossa (RIF) pain. It is based on the statistics already collected about the presence of appendicitis from patients data set of around 2230 data sets collected from BHEL Hospital, Tiruchirappalli. The conclusion is that Fuzzy logic rule based classifiers can be used an effective tool for accurately diagnosing the severity of appendicitis.