Research on Syndrome Classification Prediction Model of Tibetan Medicine Diagnosis and Treatment Based on Data Mining

Abstract

Tibetan Medicine plays an important role in traditional Chinese Medical Science. For the inheritance of Tibetan medical science and disease prevention, the main method is to summarize and study the medication and diagnostic rules by using data mining technology, which is still in the early stage. In this paper, firstly, a standard knowledge base for plateau stomach illness has been constructed by using clustering algorithm to analyze clinical diagnosis and treatment data and Tibetan medicine prescription that from "Four Medical Classics". Secondly, the classical Apriori algorithm is used to discover the associated features of disease symptoms and prescriptions. Finally, an ovel distance discriminant based K-nearest neighbor algorithm on the base of the Grey Box method is put forward to realize the Tibetan medicine diagnosis and treatment prediction model on the plateau stomach illness (Atrophic Gastritis) through combining the individual characteristics of patients and typical symptoms of plateau stomach. As a result, the model of this paper can achieve an accuracy as high as 80.1%.