The Establishment Of The Database Systems Of CHD Syndrome And The Study Of Model Of CHD Syndrome Based On BP Neural Network

Background complexity of the science is known as the 21st century science, which focus on the complexity of things, the integrity of scientific research and nonlinear methods. It provide a new perspective for the study of syndromes in Traditional Chinese Medicine. Syndrome system is a nonlinear system of the giant complex. We will be possible to achieve Syndrome research breakthroughs if we use artificial neural network technology based on the complexity of the science into Syndrome research areas. Coronary heart disease is now seriously endanger human health. At present, The large-scale data mining and the establishment of model Syndrome based onthe application of artificial neural networks for Coronary Heart Disease has yet no mature report in China.Objective We established database of syndrome of coronary heart disease system basedon the clinical epidemiology survey information, Then we constrcted the neural network model of Coronary Heart Disease syndrome using artificial neural network technology, which target to explore Syndrome research methodology and provide a new way of thinking for the current further research of syndrome。Methods We reviewed medical records of research, of coronary heart disease and analysized symptoms and signs of coronary heart disease, Then we carried out a clinical epidemiology investigation of coronary heart disease and established the database system of coronary heart disease Syndrome appling Oracle10j and Vc++6.0. On this basis, we completed syndrome BP neural network model design of coronary heart disease through gradual test, and repeated comparison of the pros and cons of five BP algorithm, select conjugate gradient algorithm as the optimal algorithm, Lastly we realized coronary heart disease Syndrome BP neural network model using MATLAB6.5, and applied to the diagnosis of coronary heart disease syndrome, the diagnosis of the model results were retrospectively tested and forward-looking test.Results We established the database systems of coronary heart disease Syndrome successfully and constrcted application the coronary heart disease Syndrome BP neural network model based on a conjugate gradient algorithm using MATLAB6.5. The model is applied to the discrimination of coronary heart disease syndromes, the results showed that:(1) In the 474 cases been collected into a retrospective examination note,429 cases are diagnosed correcttly, the judge accuracy rate is 90.5%. And the level of accuracy of was positively correlated with sample size. The judge accuracy rate in order is: Syndrome of heart Yang deficiency is93.0%, Syndrome of phlegm stasis is92.6%, Syndrome of blood stasis in heart is 91.8%, Syndrome of heart Qi deficiencyis 91.0%, Syndrome of heart Yindeficiencyisis 88.7%, and Syndrome of Qi stasis is88.6%. Syndromeof heart cold is only 37.5%,which is the minimum accuracy rate. (2) Acquisition of new cases of forward-looking examination showed:81 samples correctly identify 74 cases, and the recognition rate of 91.36%, which shows that the model can be used to explore the internal rules Syndrome.Conclusions The coronary heart disease Syndrome model based on Artificial Neural Network can be used to access the internal rules Syndrome.It is feasible to appliy artificial neural network technology into study of syndrome. The successful attempt of artificial neural network in Coronary Heart Disease Syndrome is important tostudy in depth Syndromes in heart disease syndromes real standardization and provides a new line of thought.