A Study And Application On The Clinical Classification Model For Baby Pneumonia Based On Decision Tree Algorithm

The traditional Chinese medicine is a wonderful cultural legacy of the nationalities with long history,unique theory and super effects.It's the the daughters of the the Chinese nation civilization and experience by thousands of years.The theory of traditional Chinese medicine have accumulated a great deal of datum,which contained a rich fund of knowledge.we can enrich and advance the traditional Chinese medicine's theory system with Summary and Analysis the datas. And then, the traditional Chinese medicine can can play a critical role of medical health care of all humanity. It is becoming a new researching field to explore information resources of TCM with new methods in the present age.Data Mining, dedicate to extracting the information or the knowledge which is useful, novel and could be understand by people from a mass of data. It is an advanced data processing procedure. Data Mining combines the efforts of Data Base,AI, Pattern Recognition and so on. The techniques of DM,for example,the Decision Tree, Neural Networks, Rough Set Theory and Support Vector Machine,have shown unique advantage and comprehensive applicability in the treatment of diseases and medical research.The decision tree algorithm, an analytical and predictive model to describe datum under the influence of different variables, has been successfully put to use in diagnosing and treating certain diseases. Based on the differentiation rules in traditional Chinese medicine and the requirements and characteristics of the clinical differentiation classification of the hand venule of baby pneumonia, this thesis proposes a differentiation classification model for the hand venule of baby pneumonia on the basis of the decision tree algorithm. Clinical measured data test proved that this model has a good clinical practical value, with a calculated amount relatively smaller and faster, and a classification accuracy rate over 80%.