Data Mining Technology In The Heritage Of The Clinical Experience. Name

Traditional Chinese Medicine (TCM) is the excellent cultural heritage of the Chinese nation.Today under the waves of returning to the nature, its advantages will be more and more prominent, and its status is also becoming increasingly important.TCM is a subject which requires high clinical experience.The clinical experience of the famous herbalist doctors is a summary of the practice and theory, and also a valuable treasure in development of TCM. It can not only enrich the theoretical system, but also have a tremendous role in promoting the development of TCM,if we research the academic thinking and clinical experience of the famous herbalist doctors.For the researching academic thinking and clinical experience of the famous herbalist doctors, the traditional methods have appeared inefficient, so, it is necessary to adopt modern science and technology to achieve above goal. Data mining is an efficient technology, which can be used for above goal. By data mining, academic thinking and clinical experience can be analyzed, new knowledge such as new theories and new rules can be extracted. Accordingly, clinical experience of the famous herbalist doctors can be inherited effectively.In this thesis, we focus on some mining technologies used for mining of TCM. A famous herbalist doctor's medical records about chronic gastritis are used as original data, and several applications of different algorithms are researched from different angles. In the part of mining association rules, classical algorithms of association rules such as Apriori algorithm and FP-Growth algorithm are compared, and in view of the limitation of the support-confidence algorithm, a new algorithm for mining positively correlated association rules based on Genetic Algorithms(GAs) is designed. Finally, the new algorithm and FP-Growth algorithm are used to mine association rules from medical records of chronic gastritis, and the results of both algorithms are made comparison. In the part of decision tree, ID3 algorithm and C4.5 algorithm are researched, which are very important in the decision tree. Because C4.5 algorithm has the characteristics of high accuracy and strong adapted ability, it is used in the dialectical classification of TCM. A decision tree about dialectical classification of chronic gastritis is built by using chronic gastritis dialectical data and the result is analyzed.