Data mining in meningoencephalitis: the starting point of discovery challenge

Authors:
Shusaku Tsumoto;Katsuhiko Takabayashi
Affiliations:
Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo, Japan;Division of Medical Informatics, Chiba University Hospital, Chiba, Japan
Venue:
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Year:
2011

Citing 4
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Abstract

The main difference between conventional data analysis and KDD (Knowledge Discovery and Data mining) is that the latter approaches support discovery of knowledge in databases whereas the former ones focus on extraction of accurate knowledge from databases. Therefore, for application of KDD methods, domain experts' interpretation of induced results is crucial. However, conventional approaches do not focus on this issue clearly. In this paper, 11 KDD methods are compared by using a common medical database and the induced results are interpreted by a medical expert, which enables us to characterize KDD methods more concretely and to show the importance of interaction between KDD researchers and domain experts.