SDI: Shape distribution indicator and its application to find interrelationships between physical activity tests and other medical measures

Ashkan Sami, Ryoichi Nagatomi, Makoto Takahashi, Takeshi Tokuyama

研究成果: Conference contribution

抄録

Comprehensibility is driving force in medical data mining results since doctors utilize the outputs and give the final decision. Another important issue specific to some data sets, like physical activity, is their uniform distribution due to tile analysis that was performed on them In this paper, we propose a novel data mining tool named SDI (Shape Distribution Indicator) to give a comprehensive view of co-relations of attributes together with an index named ISDI to show the robustness of SDI outputs. We apply SDI to explore the relationship of the Physical Activity data and symptoms in medical test dataset for which popular data mining methods fail to give an appropriate output to help doctors decisions. In our experiment, SDI found several useful relationships. 1 Introductio.

本文言語English
ホスト出版物のタイトルAI 2006
ホスト出版物のサブタイトルAdvances in Artificial Intelligence - 19th Australian Joint Conference on Artificial Intelligence, Proceedings
出版社Springer Verlag
ページ383-392
ページ数10
ISBN(印刷版)9783540497875
DOI
出版ステータスPublished - 2006
イベント19th Australian Joint Conference onArtificial Intelligence, AI 2006 - Hobart, TAS, Australia
継続期間: 2006 12月 42006 12月 8

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4304 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other19th Australian Joint Conference onArtificial Intelligence, AI 2006
国/地域Australia
CityHobart, TAS
Period06/12/406/12/8

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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