Patterns Exploration on Patterns of Empirical Herbal Formula of Chinese Medicine by Association Rules

BACKGROUND In this study, we use association rules to explore the latent rules and patterns of prescribing and adjusting the ingredients of herbal decoctions based on empirical herbal formula of Chinese Medicine (CM). MATERIALS AND METHODS The consideration and development of CM prescriptions based on the knowledge of CM doctors are analyzed. The study contained three stages. The first stage is to identify the chief symptoms to a specific empirical herbal formula, which can serve as the key indication for herb addition and cancellation. The second stage is to conduct a case study on the empirical CM herbal formula for insomnia. Doctors will add extra ingredients or cancel some of them by CM syndrome diagnosis. The last stage of the study is to divide the observed cases into the effective group and ineffective group based on the assessed clinical effect by doctors. The patterns during the diagnosis and treatment are selected by the applied algorithm and the relations between clinical symptoms or indications and herb choosing principles will be selected by the association rules algorithm. RESULTS Totally 40 patients were observed in this study: 28 patients were considered effective after treatment and the remaining 12 were ineffective. 206 patterns related to clinical indications of Chinese Medicine were checked and screened with each observed case. In the analysis of the effective group, we used the algorithm of association rules to select combinations between 28 herbal adjustment strategies of the empirical herbal formula and the 190 patterns of individual clinical manifestations. During this stage, 11 common patterns were eliminated and 5 major symptoms for insomnia remained. 12 association rules were identified which included 5 herbal adjustment strategies. CONCLUSION The association rules method is an effective algorithm to explore the latent relations between clinical indications and herbal adjustment strategies for the study on empirical herbal formulas.