Research of TCM Syndromes Diagnostic Models for Chronic Gastritis Based On Multielement Mathematical Statistical Methods
In this study, we assessed the large sample population of patients with chronic gastritis based on three methods with supervised learning function, i.e., the regression analysis, BP neural network and Support Vector Machine. On basis of the results, we constructed the diagnostic models to predict the types of Traditional Chinese Medicine (TCM) syndromes of chronic gastritis, and compared the correct rate and applicability of each method. The study showed the correct rate of prediction was as follows: Support Vector Machine > BP neural network > regression analysis, after construction of diagnostic models with three algorithms. We believe, our results could be of great value in exploring the methodology of objectification and standardization of TCM Syndromes.
WANG Yi-qin LI Fu-feng YAN Hai-xia LIU Guo-ping XIA Chun-ming XU Zhao-xia FU Jing-jing WANG Xue-hua DENG Feng YE Jin HE Jian-cheng
Shanghai Uiversity of Traditional Chinese Medicine; Shanghai 201203 East China University of Science and Technology, Shanghai 200237
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
31-37
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）