title: [Application of Bayesian network in syndrome differentiation system of traditional Chinese medicine].
abstract: The concept of syndrome in traditional Chinese medicine (TCM) is a nonlinear, open and complicated huge system. Syndrome differentiation in TCM belongs to cognitive and noetic science. To establish a new syndrome differentiation system based on the key elements of the syndrome is necessary for TCM practitioners to promote differentiation ability and reach consensus on differentiation method. With combination of experience and computation models, the Bayesian network was used in the study of the relationship between the key elements of syndrome and the symptoms, and the relationship among different key elements, in which the computing diagnosis result was identical to the result from an experienced TCM doctor. The study showed that Bayesian network is a good method to deal with the information of symptoms and signs for syndrome differentiation, but it is also not to reflect comprehensively the thinking ability of TCM doctors in doing syndrome differentiation.
authors.affiliation: Institute of Traditional Chinese Medicine Diagnosis, Hunan University of Traditional Chinese Medicine, Changsha, Hunan Province 410007, China. zwf1189@yahoo.com.cn
authors.forename: Wen-Feng
authors.initials: WF
authors.lastname: Zhu
authors.forename: Jun-Feng
authors.initials: JF
authors.lastname: Yan
authors.forename: Bi-Qun
authors.initials: BQ
authors.lastname: Huang
mesh_terms: D001499:Bayes Theorem; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D005103:Expert Systems; D006801:Humans; D008516:Medicine, Chinese Traditional / Q000379:methods*