Diagnostic system of mild cognitive impairment based on Bayesian network

Yan Sun, Yi Yuan Tang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper presents a new method in structure learning of Bayesian network based on dependency analysis and scoring function. Through analyzing the dependent relationship between variables and accessing to undirected graph, the prior sequence of all of the nodes in Bayesian network structure is obtained. The optimal structure of the Bayesian network is then generated by heuristic-search method. The new algorithm has been applied to the diagnostic system of mild cognitive impairment. The experimental results show that the new algorithm can better predict the possibility of mild cognitive impairment under the similar complexity, and further assist the diagnosis of doctor.

Original languageEnglish
Pages (from-to)336-341
Number of pages6
JournalDianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China
Volume41
Issue number3
DOIs
StatePublished - May 2012

Keywords

  • Bayesian network
  • Dependency analysis
  • Diagnostic system
  • Mild cognitive impairment

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