title: Mathematical modeling of sign-and-symptom-oriented diagnostic procedure in traditional Chinese medicine based on the analytic hierarchy process: indications of Guizhi Decoction and its varieties in the Shanghanlun.
abstract: OBJECTIVE
  This study explores the applicability of a multi-attribute decision-making method in assessing Guizhi Decoction (GZD) and its varieties as noted in the Shanghanlun.
  
  
  METHODS
  A known multi-attribute decision-making method, the analytic hierarchy process (AHP), was adopted to transform the clinical challenge of selecting optional decoction for a given combination of symptoms or signs into multiple criteria decision-making problem.
  
  
  RESULTS
  A normative model based on the AHP was realized for indications of GZD and its varieties. The indications of sub-family GZD-f (indications of GZD itself) were exterior illness; the indications of GZD-vf1 (indications of GZD's variants which consist of fine adjustments to the ingredients or content on the basis of GZD) were exterior illness with interior excess, suggesting that GZD-vf1 consisted of most conservative variants of GZD; the indications of both GZD-vf2 (indications of Guizhi Qu Shaoyao Decoction and its derivative variants) and GZD-vf3 (indications of Guizhi Gancao Decoction and its derivative variants) showed evolution from exterior illness to interior deficiency in 2 directions. As to efficacy evaluation of the decoction, GZD and its varieties (restricted to those comparable ones) were of equal efficacy on 3 popular signs or symptoms indicating exterior illness: floating pulse, aversion to wind and spontaneous sweating, which were the common ground of indications for the GZD family.
  
  
  CONCLUSIONS
  Modeling of diagnostic procedure based on the AHP is proved practicable to analyze the clinical judgment system of traditional Chinese medicine. Quantification research on syndrome differentiation and decoction evaluation system focused on signs and symptoms is suggested as a feasible and reliable model.
authors.affiliation: Department of Traditional Chinese Medicine, Jinan University, Guangdong Province, China. doctorpanpanpan@yahoo.com.cn
authors.forename: Da-wei
authors.initials: DW
authors.lastname: Pan
authors.forename: Li-guo
authors.initials: LG
authors.lastname: Chen
mesh_terms: D003657:Decision Making; D004365:Drugs, Chinese Herbal; D008516:Medicine, Chinese Traditional / Q000379:methods*; D008962:Models, Theoretical
chemical_list: D004365:Drugs, Chinese Herbal; C528663:guizhi decoction