Proposal of medical KDD support user interface utilizing rule interestingness measures

Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper discusses the utilization of rule interestingness measures in medical KDD. We selected various interestingness measures and conducted experiments using clinical datasets to examine how they can estimate real human interest. The results indicate that some of them have a stable, reasonable estimation performance and the combinational use of interestingness measures will contribute to medical KDD. We then developed a prototype of medical KDD support user interface based on the experimental outcomes. We conducted a case study in which a medical expert tried to discover medical knowledge with the prototype. Some interesting rules were actually obtained and that indicates the potential of the user interface.

Original languageEnglish
Title of host publicationProceedings - ICDM Workshops 2006 - 6th IEEE International Conference on Data Mining - Workshops
Pages759-764
Number of pages6
Publication statusPublished - 2006 Dec 1
Event6th IEEE International Conference on Data Mining - Workshops, ICDM 2006 - Hong Kong, China
Duration: 2006 Dec 182006 Dec 18

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other6th IEEE International Conference on Data Mining - Workshops, ICDM 2006
CountryChina
CityHong Kong
Period06/12/1806/12/18

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ohsaki, M., Abe, H., Tsumoto, S., Yokoi, H., & Yamaguchi, T. (2006). Proposal of medical KDD support user interface utilizing rule interestingness measures. In Proceedings - ICDM Workshops 2006 - 6th IEEE International Conference on Data Mining - Workshops (pp. 759-764). [4063727] (Proceedings - IEEE International Conference on Data Mining, ICDM).