African Journal of
Pharmacy and Pharmacology

  • Abbreviation: Afr. J. Pharm. Pharmacol.
  • Language: English
  • ISSN: 1996-0816
  • DOI: 10.5897/AJPP
  • Start Year: 2007
  • Published Articles: 2284

Full Length Research Paper

Statistical analysis of medical experiment data for discovering groups of correlated symptoms

Chenghe Shi1#, Qingqiong Deng2#, Peng Lu3#, Minquan Zhou2 and Gang Xiong4*
1Department of Traditional Chinese Medicine, Peking University Third Hospital, Beijing 100191, P. R. China. 2College of Information Science and Technology, Beijing Normal University, No. 19 Xin-Jie-Kou-Wai Street, Beijing 100875, P.R China. 3Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P. R. China. 4Department of Physics, Beijing Normal University, No. 19 Xin-Jie-Kou-Wai Street, Beijing 100875, P. R. China.
Email: [email protected]

  •  Accepted: 03 May 2012
  •  Published: 15 July 2012

Abstract

Three ways of statistical analysis, that is, Pearson correlation (PC), Spearman correlation (SC) and mutual information (MI), are applied on medical experiment data to obtain correlation matrix. When the results of this study’s analysis were combined with those of professional analysis, it was found that the method based on MI may be the best way for discovering groups of correlated symptoms.

 

Key words: Association, symptom combination, coronary heart disease.

Copyright © 2024 Author(s) retain the copyright of this article.

This article is published under the terms of the Creative Commons Attribution License 4.0

Back to Vol. 6 No. 26
Back to articles
  • Articles on Google by:
SUBSCRIBE TO RSS
SUBMIT MANUSCRIPT
CONFERENCES