BUILDING AND EVALUATING AN ANIMAL MODEL FOR SYNDROME IN TRADITIONAL CHINESE MEDICINE IN THE CONTEXT OF UNSTABLE ANGINA (MYOCARDIAL ISCHEMIA) BY SUPERVISED DATA MINING APPROACHES

Building an animal model for a disease is a better avenue to understand the inner mechanism of it. Traditional Chinese Medicine accumulated much practical experience and a large amount of literature to heal diseases during the past 3000 years. However, as there is no available animal model for TCM research because syndrome, the core of TCM theory, it is hard to be diagnosed from animals. In this paper, we present a novel strategy to build and evaluate an animal model for syndrome in TCM in the context of a disease. We first carried out a clinical epidemiology survey for a syndrome ( Blood stasis syndrome, BSS) diagnosed by TCM experts in the context of a disease ( Unstable angina, UA). Meanwhile, the blood samples of patients included in the survey were collected and measured as physical and chemical specifications by laboratory examinations. Alternatively, we used supervised data mining methods to build association between the specifications and the syndrome in the context of UA. The accuracy of classification was used to evaluate performance of the association built. Finally, we built an animal model for myocardial ischemia and validated the model by established diagnosis criterion of myocardial ischemia. Furthermore, the built association was used to evaluate whether an animal is with BSS. The results indicated that the strategy successfully evaluates and separates the animal model for syndrome in TCM from the counterpart for myocardial ischemia. The novel strategy presented in the paper provides a better insight to understand the nature of syndrome in TCM and pave a basis for personalized therapies of UA.