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Discovery of Trends and States in Irregular Medical Temporal Data

  • Trong Dung Nguyen
  • Saori Kawasaki
  • Tu Bao Ho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2843)

Abstract

Temporal abstraction has been known as a powerful approach of data abstraction by converting temporal data into interval with abstracted values including trends and states. Most temporal abstraction methods, however, has been developed for regular temporal data, and they cannot be used when temporal data are collected irregularly. In this paper we introduced a temporal abstraction approach to irregular temporal data inspired from a real-life application of a large database in hepatitis domain.

Keywords

Interferon Therapy Change Test Temporal Abstraction Data Mining System Abstraction Method 
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 2003

Authors and Affiliations

  • Trong Dung Nguyen
    • 1
  • Saori Kawasaki
    • 1
  • Tu Bao Ho
    • 1
  1. 1.Japan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan

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