Discovery of Association Rules between TCM Properties in Drug Pairs by Association Mining between Datasets and Probability Tests

Crude Drug Pairs in Traditional Chinese medicine (TCM) constitute an important link node between TCM drugs and medicinal formulae. In TCM theory, there are many descriptions regarding the multiple aspects of medicines. However, they seem still scattered compared to the formulae theories. In this article, the association-rule mining method was applied to discover the meaningful associations with reference to the structure of a crude drug-pair. Standard and enhanced Apriori algorithms were applied and run on the crude drug-pair database, including 625 drug pairs, 347 drugs, and 49 properties. The results from the two algorithms were compared and analyzed, and the new enhanced Apriori algorithm was found to be more suitable for the detection of association between drugs in a drug pair or formulae.