Study on intelligent syndrome differentiation in Traditional Chinese Medicine based on information fusion technology

摘要

Objective: Establish four-diagnosis syndrome differentiation model of Traditional Chinese Medicine (TCM) based on information fusion technology (four diagnostic methods refer to inspection, auscultation and olfaction, inquiry and pulse-taking. Method: Apply the objective detection instruments of four-diagnostic method to collect four-diagnosis objective information of 509 cases of clinical heart-system patients, then adopt multiple artificial neural network of single output and multiple- support vector machine to establish recognition model of syndrome above. Result: Recognition rates of the 6 syndromes, Deficiency of Heart Qi, Deficiency of Heart Yang, Deficiency of Heart Yin, Phlegm, blood stasis, Stagnation of Qi, by multiple artificial neural network of single output, are respectively 60.67%, 78.08%, 65.16%, 60.11%, 62.35% and 87.07%, whereas, by multi-class support vector machine, respectively 73.20%, 81.70%, 68.63%, 50.33%, 76.47%, 85.62%. Conclusion: TCM four-diagnosis syndrome differentiation model set up based on SVM is of high quality with compare with artificial neural network.