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Recognition Patterns Construction of Coronary Heart Disease Patients with Qi Deficiency Syndrome Based on Artificial Neural Network

Coronary heart disease (CHD), called “thoracic obstruction” in TCM, is one of the most important types of heart disease for its high incidence and mortality. The methods of syndrome studies in TCM can not be completely in accordance with these of modern medicine because of the complexity itself. In this paper, we investigated the ability of Artificial Neural Networks (ANNs) to predict CHD patients with or without qi deficiency syndrome. Predictions with Multilayer Perceptron Neural Network (MPLNN, one type of the ANNS), we obtained recognition patterns made up of eight biological parameters. The accuracy of this recognition pattern was 82.2%, and the accuracy of validation pattern was 80.0%.