Title page for etd-0802100-164752


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URN etd-0802100-164752
Author Chih-Hung Chiu
Author's Email Address m8742612@student.nsysu.edu.tw
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Department Information Management
Year 1999
Semester 2
Degree Master
Type of Document
Language English
Title Using Bayesian Networks for Discovering Temporal-State Transitions in Hemodialysis
Date of Defense 2000-07-27
Page Count 52
Keyword
  • Hemodialysis
  • knowledge management
  • Bayesian network
  • data mining
  • Abstract  In this thesis, we discover knowledge from workflow logs with temporal-state transitions in the form of Bayesian networks. Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest, and easily incorporates with new instances to maintain rules up to date. The Bayesian networks can predict, communicate, train, and offer more alternatives to make better decisions. We demonstrate the proposed method in representing the causal relationships between medical treatments and transitions of patient’s physiological states in the Hemodialysis process. The discovery of clinical pathway patterns of Hemodialysis can be used for predicting possible paths for an admitted patient, and facilitating medical professionals to control the Hemodialysis machines during the Hemodialysis process. The reciprocal knowledge management can be extended from the results in future research.
    Advisory Committee
  • Chih-Ping Wei - chair
  • San-Yih Hwang - co-chair
  • Fu-Ren Lin - advisor
  • Files
  • 8742612.pdf
  • indicate access worldwide
    Date of Submission 2000-08-02

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