A Hybrid Data Mining Approach for Knowledge Extraction and Classification in Medical Databases

Authors:
Syed ZahidHassan;Brijesh Verma
Affiliations:
-;-
Venue:
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
Year:
2007

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Abstract

This paper presents a novel hybrid data mining approach for knowledge extraction and classification in medical databases. The approach combines self organizing map, k-means and naïve bayes with a neural network based classifier. The idea is to cluster all data in soft clusters using neural and statistical clustering and fuse them using serial and parallel fusion in conjunction with a neural classifier. The approach has been implemented and tested on a benchmark medical database. The preliminary experiments are very promising.