title: Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods.
abstract: OBJECTIVE
  To provide the distribution pattern and compatibility laws of the constituent herbs in prescriptions, for doctor's convenience to make decision in choosing correct herbs and prescriptions for treating respiratory disease.
  
  
  METHODS
  Classical prescriptions treating respiratory disease were selected from authoritative prescription books. Data mining methods (frequent itemsets and association rules) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions.
  
  
  RESULTS
  A total of 562 prescriptions were selected to be studied. The result exhibited that, Radix glycyrrhizae was the most frequently used in 47.2% prescriptions, other frequently used were Semen armeniacae amarum, Fructus schisandrae Chinese, Herba ephedrae, and Radix ginseng. Herbal ephedrae was always coupled with Semen armeniacae amarum with the confidence of 73.3%, and many herbs were always accompanied by Radix glycyrrhizae with high confidence. More over, Fructus schisandrae Chinese, Herba ephedrae and Rhizoma pinelliae was most commonly used to treat cough, dyspnoea and associated sputum respectively besides Radix glycyrrhizae and Semen armeniacae amarum. The prescriptions treating dyspnoea often used double herb group of Herba ephedrae & Radix glycyrrhizae, while prescriptions treating sputum often used double herb group of Rhizoma pinelliae & Radix glycyrrhizae and Rhizoma pinelliae & Semen armeniacae amarum, triple herb groups of Rhizoma pinelliae & Semen armeniacae amarum & Radix glycyrrhizae and Pericarpium citri reticulatae & Rhizoma pinelliae & Radix glycyrrhizae.
  
  
  CONCLUSIONS
  The prescriptions treating respiratory disease showed common compatibility laws in using herbs and special compatibility laws for treating different respiratory symptoms. These principle patterns and special compatibility laws reported here could be useful for doctors to choose correct herbs and prescriptions in treating respiratory disease.
authors.affiliation: School of Information Management, Shandong University of Traditional Chinese Medicine, Jinan 250355, China. xianxiu@hotmail.com
authors.forename: Xian-Jun
authors.initials: XJ
authors.lastname: Fu
authors.forename: Xu-Xia
authors.initials: XX
authors.lastname: Song
authors.forename: Lin-Bo
authors.initials: LB
authors.lastname: Wei
authors.forename: Zhen-Guo
authors.initials: ZG
authors.lastname: Wang
mesh_terms: D057225:Data Mining / Q000379:methods*; D004338:Drug Combinations; D011307:Drug Prescriptions / Q000145:classification*; D004359:Drug Therapy, Combination / Q000379:methods; D004365:Drugs, Chinese Herbal / Q000008:administration & dosage / Q000145:classification*; D041743:Herb-Drug Interactions / Q000502:physiology; D006801:Humans; D008516:Medicine, Chinese Traditional / Q000379:methods*; D012140:Respiratory Tract Diseases / Q000188:drug therapy* / Q000453:epidemiology; D012196:Review Literature as Topic
chemical_list: D004338:Drug Combinations; D004365:Drugs, Chinese Herbal