부산대학교 도서관

Herbal Medicine in Traditional Chinese Medicine (TCM) relies on interactions between ingredients of a prescription. The combination is chosen to promote desirable interactions. Analysing these interactions is important in quantitatively analysing effects of TCM on patient outcomes. The concept of interactions has not been adequately formulated before due to the ambiguity of “interaction” and the need to go beyond traditional quantitative methods for analysis. In this working paper, we present an exploratory analysis of clinical records using an interaction pattern mining approach. We present the most significant interactions found with a summary of clinical significance. Our experimental evaluation confirms this approach is able to detect effective high-order herb-herb interactions in TCM datasets. The interaction mining approach can be a potentially useful technique for discovering interactions not detected by other techniques. The results have implications for better understanding of the mechanisms of action and overall system effects.