Analysis on composition rules of suppress cough based on association rules and clustering algorithm

Abstract

Objective To explore composition rules of suppress cough prescriptions. Methods The suppress cough prescriptions in New National Medicine were collected to build a database based on Traditional Chinese medicine inheritance assist system. The methods of association rules with apriori algorithm and complex system entropy cluster were used to achieve the frequency of medicines and association rules between drugs. Results The data-mining results indicated that the most frequently used drugs were Glycyrrhizae, Platycodon Semen armeniacae Ephdra vulgaris, tangerine or orange peel. The most frequent drug combinations were Radix Glycyrrhizae, Platycodon grandiflorum, Radix Glycyrrhizae, Semen armeniacae amarae, Radix Glycyrrhizae, tangerine or orange peel and so on. The drugs with a high degree confidence coefficient of association rules include Dried tangerine or orange peel, the root bark of white mulberry, Dried tangerine or orange peel, Snakegourd Seed. The new prescription that we can get composited by Fructus Aurantii was Angelica decursiva, Pericarpium Citri Reticulatae, Rhizoma Anemarrhenae, the root bark of white mulberry. Conclusion From the analysis above, we could conclude that the drugs in suppress cough prescriptions have more effects of relieving superficies, clearing heat and drying dampness, ventilating the lung and resolving phlegm, nourishing Yin and supplementing Qi. Key words: Suppressing-cough prescription; Association rules; Clustering algorithm