• DocumentCode
    2380275
  • Title

    Association analysis and distribution of chronic gastritis syndromes based on associated density

  • Author

    Liu, Guo-Ping ; Wang, Yi-Qin ; Li, Fu-Feng ; Yan, Hai-Xia ; Fu, Jing-Jing ; Zhao, Jie ; Zhen, Rui-Wen ; Yan, Shi-Xing ; Li, Guo-Zheng

  • Author_Institution
    Lab. of Inf. Access & Synthesis of TCM Four Diagnosis, Shanghai Univ. of Traditional Chinese Med., Shanghai, China
  • fYear
    2010
  • fDate
    18-18 Dec. 2010
  • Firstpage
    790
  • Lastpage
    794
  • Abstract
    Purpose: The analysis of syndrome distribution and the association between syndrome-syndrome in chronic gastritis (CG) patients can provide references for research about Traditional Chinese Medicine (TCM) diagnosis and treatment of CG. Method: This paper applies the investigation method of clinical epidemiology, adopts probability statistics method and comes up with the concept of associated density to conduct association analysis of syndromes. Result: In the distribution of syndromes patients who have a single syndrome occupy 64.7% of the whole sample; patients who have two syndromes make up 32.2%; the situation that 3 syndromes happen at the same time has a percentage of 1.3%.spleen-stomach qi deficiency syndrome and liver qi stagnation syndrome are closely associated. Conclusion: Liver and spleen are the main disease locations of CG and these two organs are associated with and influenced each other in physiology and pathology.
  • Keywords
    data mining; diseases; liver; medical diagnostic computing; patient treatment; probability; TCM; associated density; association analysis; chronic gastritis; chronic gastritis syndromes; liver qi stagnation syndrome; probability statistics method; spleen-stomach qi deficiency syndrome; traditional Chinese medicine; association; chronic gastritis; distribution; syndrome;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
  • Conference_Location
    Hong, Kong
  • Print_ISBN
    978-1-4244-8303-7
  • Electronic_ISBN
    978-1-4244-8304-4
  • Type

    conf

  • DOI
    10.1109/BIBMW.2010.5703912
  • Filename
    5703912