Research On Chronic Gastritis Syndromes Of TCM Inquiry Based On Extreme Learning Machine

Usually the main form of interrogation in TCM is based on the patient’s condition, to carry out the artificial judgment to ask the patient symptom related information, in this way not only has strong subjectivity, and prone to errors of judgment, resulting in the treatment of errors. With the development of computer technology, especially the computer technology applied to medicine, the research level of medicine is greatly improved, also let the previous by virtue of experience knowledge gradually systematization, objectification. The information technology to study TCM interrogation of chronic gastritis data, using feature selection to reduce data set, and use classification of chronic gastritis data set to divide the work.The main work of this paper is as follows:(1) To propose the ReliefF&Rough set for interrogation in TCM feature selection method, on the results of feature selection are analyzed according to the theory of traditional Chinese medicine (TCM). The result is basically of chronic gastritis in TCM theory and clinical practice and anastomosis.(2) Based on ReliefF&Roughset of the feature selection, the use of extreme learning machine algorithm for modeling of chronic gastritis in TCM interrogation of data and achieved better classification results.(3) The classification performance of the Set ReliefF &Rough and the limit learning machine and the other multi label classification algorithms are compared with the experimental analysis. The effect of the algorithm is also tested by using statistical analysis and score. Through experimental analysis, we can see the ReliefF&Rough set and limit learning machine algorithm has good adaptability to chronic gastritis data sets, and can effectively improve the effect of classification data set and for future research work to bring new technology direction.