Multi-aspect Hepatitis Data Analysis(Medical Active Mining)

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概要

• 論文の詳細を見る

• When IFN (interferon) is used for chronic hepatitis patients, various conceptual knowledge/rules will benefit for giving a treatment. In this paper, we describe an ongoing work on using various data mining agents including the GDT-RS inductive learning system for discovering classification rules, and the LOI (learning with ordered information) for discovering important features, in a multi-phase process for multi-aspect analysis of the hepatitis data. Our methodology and experimental results show that the perspective of doctors will be changed from a single type of experimental data analysis towards a holistic view, by using our multi-aspect mining approach.

• 一般社団法人情報処理学会の論文
• 2004-12-04

著者

• Yokoi Hideto

  School Of Medicine Chiba University

• Fujita Yasuo

  Department Of Information Engineering Maebashi Institute Of Technology

• Ohshima Muneaki

  Department Of Information Engineering Maebashi Institute Of Technology

• ZHONG NlNG

  Department of Information Engineering, Maebashi Institute of Technology

• Zhong Nlng

  Department Of Information Engineering Maebashi Institute Of Technology

関連論文

• Multi-aspect Hepatitis Data Analysis(Medical Active Mining)
• Multi-aspect Hepatitis Data Analysis(Medical Active Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)

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