Abstract :
Objective: Based on the Apriori algorithm, we develop a method for mining traditional Chinese medicine herb prescriptions. Procedures and Methods: input the 1,632 medical records of Chen Shouqiang, Associate Chief Physician, into the electronic medical records management system; mine the high-frequency combination of traditional Chinese medicine for treatment of coronary heart disease via the Apriori algorithm; take the combination with most kinds of herbal medicines as the motherboard, and then add Chinese medicine different from what included in the top N groups of high-frequency combinations of traditional Chinese medicine; thus we can sum up the empirical formula. Results: the empirical formula mined consists of 12 herbs (i.e. rhizome of Ligusticum wallichii, salvia miltiorrhiza, tuber of dwarf lilyturf, Costustoot, licorice Roots Northwest Origin, Schisandra chinensis, Coptis chinensis, Scutellaria baicalensis, charred triplet, fructus forsythiae, cuttlebone and radix astragali), which is similar with the chest stuffiness No. 2 formula commonly used in clinic. Conclusion: This method has some significance in the experience heritage of distinguished veteran doctors of TCM, and it is worth promoting.
Keywords :
data mining; electronic health records; medicine; patient treatment; Apriori algorithm; chest stuffiness; clinic; coronary heart disease treatment; electronic medical records management system; empirical formula; herbal medicines; high frequency combination; traditional Chinese medicine herb prescription mining; veteran doctors; Blood; Databases; Diseases; Educational institutions; Heart; Medical diagnostic imaging; Apriori algorithm; data mining; distinguished veteran doctors of TCM; empirical formula;
