Application Studies of Bayes Discriminant and Cluster in TCM Acupuncture Clinical Data Analysis

  • Xiangyang Feng
  • Youqun Shi
  • Qinfeng Huang
  • Wenli Cheng
  • Houqin Su
  • Jie Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

For the acupuncture clinical big samples’ data, Bayes discriminant method has been studied and applied to determine comprehensive posterior treatment effects of the same disease samples, and a K-mean cluster algorithm with a tolerance value has been proposed and applied to classify the samples based on a transmutative Euclidean distance function which is proposed in this paper. Differences in terms of acupuncture points and posterior treatment effective gradations between pair of samples are originally introduced into an Euclidean distance function. The analysis methods studied in this paper can service scientific analysis on acupuncture clinical data and provide a newest research way to estimate qualities of TCM acupuncture clinical treatment cases presented in the literatures.

Keywords

Traditional chinese medicine Clinical data Acupuncture point Treatment effect Euclidean distance calculating formula Estimation Discriminant and cluster analysis 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Xiangyang Feng
    • 1
  • Youqun Shi
    • 1
  • Qinfeng Huang
    • 2
  • Wenli Cheng
    • 1
  • Houqin Su
    • 1
  • Jie Liu
    • 2
  1. 1.College of Computer Science and TechnologyDonghua UniversityShanghaiPeople’s Republic of China
  2. 2.Shanghai Institute of Acupuncture and MeridianShanghaiPeople’s Republic of China

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