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: 2288

Full Length Research Paper

Unsupervised data mining technology based on research of stroke medication rules and discovery of prescription

Xinjie Li1,2, Mingqi Wang3, Xujie Yu3, Xiaoyan Li3, Jingwei Liu3, Zhenhua Jia1,4* and Wei Cong5
1Hebei Yiling Medicine Research Institute, Shijiazhuang 050035, China. 2Key Laboratory of collateral disease of Hebei Province, Shijiazhuang 050035, China. 3Beijing University of Chinese Medicine, Beijing 100029, China. 4Hebei Yiling Hospital Cardiovascular Division, Shijiazhuang 050091, China. 5Key Research Centre of State Administration of Traditional Chinese Medicine (Collateral Disease of Cardiovascular/TCM Collateral Disease Theory Key discipline of State Administration of TCM of China), Shijiazhuang 050035, China.
Email: [email protected]

  •  Accepted: 01 June 2012
  •  Published: 08 August 2012

Abstract

For collecting and sorting literature on treatment of ancient and modern stroke at the entry point, frequency and charts analysis methods were applied. Modern computer technology and statistics were used to do in-depth study of stroke literature data, explore stroke differentiation of symptoms and signs and regular treatment by ancient physicians. On this basis, the unsupervised data mining technology was applied to obtain each syndrome commonly used for drug pair and combination of core. In assembling empirically drug pair and combination of core, 3 new prescriptions were obtained for each syndrome.


Key words: Unsupervised data mining, stroke, medication rules, new prescription.