title: Syndrome classification based on manifold ranking for viral hepatitis.
abstract: Treatment determination based on syndrome differentiation is the key of Chinese medicine. A feasible way of improving the clinical therapy effectiveness is needed to correctly differentiate the syndrome classifications based on the clinical manifestations. In this paper, a novel data mining method based on manifold ranking (MR) is proposed to explore the relation between syndromes and symptoms for viral hepatitis. Since MR could take the symptom data with expert differentiation and the symptom data without expert differentiation into the task of syndrome classification, the clinical information used for modeling the syndrome features is greatly enlarged so as to improve the precise of syndrome classification. In addition, the proposed method of syndrome classification could also avoid two disadvantages in previous methods: linear relation of the clinical data and mutually exclusive symptoms among different syndromes. And it could help exploit the latent relation between syndromes and symptoms more effectively. Better performance of syndrome classification is able to be achieved according to the experimental results and the clinical experts.
authors.affiliation: Clinical Evaluation Center, Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
authors.forename: Yu-feng
authors.initials: YF
authors.lastname: Zhao
authors.forename: Li-yun
authors.initials: LY
authors.lastname: He
authors.forename: Bao-yan
authors.initials: BY
authors.lastname: Liu
authors.forename: Jun
authors.initials: J
authors.lastname: Li
authors.forename: Feng-yi
authors.initials: FY
authors.lastname: Li
authors.forename: Rui-li
authors.initials: RL
authors.lastname: Huo
authors.forename: Xiang-hong
authors.initials: XH
authors.lastname: Jing
mesh_terms: D006525:Hepatitis, Viral, Human / Q000145:classification*; D006801:Humans; D008516:Medicine, Chinese Traditional