Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an Interferon Therapy Risk Mining for Chronic Hepatitis

  • Hidenao Abe
  • Miho Ohsaki
  • Hideto Yokoi
  • Takahira Yamaguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4012)


In this paper, we present the implementation of an integrated time-series data mining environment. Time-series data mining is one of key issues to get useful knowledge from databases. With mined time-series patterns, users can aware not only positive results but also negative result called risk after their observation period. However, users often face difficulties during time-series data mining process for data pre-processing method selection/construction, mining algorithm selection, and post-processing to refine the data mining process as other data mining processes. It is needed to develop a time-series data mining environment based on systematic analysis of the process. To get more valuable rules for domain experts from a time-series data mining process, we have designed an environment which integrates time-series pattern extraction methods, rule induction methods and rule evaluation methods with active human-system interaction. After implementing this environment, we have done a case study to mine time-series rules from blood and urine biochemical test database on chronic hepatitis patients. Then a physician has evaluated and refined his hypothesis on this environment. We discuss the availability of how much support to mine interesting knowledge for an expert.


Chronic Hepatitis Domain Expert Rule Induction Pattern Extraction Data Mining Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hidenao Abe
    • 1
  • Miho Ohsaki
    • 2
  • Hideto Yokoi
    • 3
  • Takahira Yamaguchi
    • 4
  1. 1.Department of Medical InformaticsShimane University, School of Medicine 
  2. 2.Faculty of EngineeringDoshisha University 
  3. 3.Department of Medical InformaticsKagawa University Hospital 
  4. 4.Faculty of Science and TechnologyKeio University 

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