A TCM Syndrome Differentiation Algorithm based on Deep Belief Network

The application of deep learning algorithm in the field of TCM diagnosis and treatment provides a reference for exploring the law of TCM syndrome differentiation. In view of the complicated relationship between symptoms and syndromes in TCM clinical syndrome differentiation model and the long training time of the model, etc. A deep belief network RBM mechanism is proposed to fit samples to obtain optimal weights and thresholds. Multi-label classification algorithms have been used in solve the one-to-many problem between symptoms and syndromes. The clinical syndrome differentiation model of traditional Chinese medicine is applied to the actual system to assist doctors to inquire and diagnose and improve the accuracy of diagnosis results.