Integration of Data Mining and Hybrid Expert System

I. G. L. da Silva, B. P. Amorim, P.G. Campos, and L. M. Brasil

In the latest decades a great growth in the capacity of generating and collecting data has happened. The progresses in the data collection and storage, combined with the extensive use of the Database Management System and Data Warehousing technology, have contributed to this growth. However, the traditional methods used to manipulate these data can generate informative reports, but they cannot analyze the content of the data to point out what knowledge interests most. These difficulties contributed to the arising of intelligent tools and techniques to analyze data resultant from the emergent field of the Knowledge Discovery in Databases (KDD). KDD is not a trivial process and it is used to identify valid, potentially useful and comprehensible patterns in the database. The main goals of this work are to apply some of these tools and techniques to a medical database of breast cancer, so that detection and prediction patterns are discovered, and use the database resulting of the mining process in a hybrid expert system that will help in medical diagnosis.

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