Investigation of rule interestingness in medical data mining

Miho Ohsaki, Shinya Kitaguchi, Hideto Yokoi, Takahira Yamaguchi

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

7 Citations (Scopus)

Abstract

This research experimentally investigates the performance of conventional rule interestingness measures and discusses their usefulness for supporting KDD through human-system interaction in medical domain. We compared the evaluation results by a medical expert and those by selected sixteen kinds of interestingness measures for the rules discovered in a dataset on hepatitis. χ2 measure, recall, and accuracy demonstrated the highest performance, and specificity and prevalence did the lowest. The interestingness measures showed a complementary relationship for each other. These results indicated that some interestingness measures have the possibility to predict really interesting rules at a certain level and that the combinational use of interestingness measures will be useful. We then discussed how to combinationally utilize interestingness measures and proposed a post-processing user interface utilizing them, which supports KDD through human-system interaction.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages174-189
Number of pages16
Volume3430 LNAI
Publication statusPublished - 2005
EventSecond International Workshop on Active Mining, AM 2003 - Maebashi, Japan
Duration: 2003 Oct 282003 Oct 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3430 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherSecond International Workshop on Active Mining, AM 2003
CountryJapan
CityMaebashi
Period03/10/2803/10/31

Fingerprint

Data Mining
User interfaces
Data mining
Processing
Hepatitis
Research
Interaction
Post-processing
User Interface
Specificity
Lowest
High Performance
Predict
Evaluation
Datasets

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Ohsaki, M., Kitaguchi, S., Yokoi, H., & Yamaguchi, T. (2005). Investigation of rule interestingness in medical data mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3430 LNAI, pp. 174-189). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3430 LNAI).

Investigation of rule interestingness in medical data mining. / Ohsaki, Miho; Kitaguchi, Shinya; Yokoi, Hideto; Yamaguchi, Takahira.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3430 LNAI 2005. p. 174-189 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3430 LNAI).

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

Ohsaki, M, Kitaguchi, S, Yokoi, H & Yamaguchi, T 2005, Investigation of rule interestingness in medical data mining. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3430 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3430 LNAI, pp. 174-189, Second International Workshop on Active Mining, AM 2003, Maebashi, Japan, 03/10/28.
Ohsaki M, Kitaguchi S, Yokoi H, Yamaguchi T. Investigation of rule interestingness in medical data mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3430 LNAI. 2005. p. 174-189. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Ohsaki, Miho ; Kitaguchi, Shinya ; Yokoi, Hideto ; Yamaguchi, Takahira. / Investigation of rule interestingness in medical data mining. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3430 LNAI 2005. pp. 174-189 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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