Syndrome Classification Based on Manifold Ranking for Viral Hepatitis  

作　　者：赵玉凤 何丽云 刘保延 李筠 李丰衣 霍蕊莉 景向红 

机构地区：[1]Clinical Evaluation Center,Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences [2]China Academy of Chinese Medical Sciences [3]Infectious Disease Clinics and Research Centers,People's Liberation Army 302Hospital [4]Institute of Acupuncture and Moxibustion,China Academy of Chinese Medical Sciences

出　　处：《Chinese Journal of Integrative Medicine》2014年第5期394-399,共6页中国结合医学杂志（英文版）

基　　金：Supported by National Natural Science Foundation of China(No.81202858);National Key Technology Support Program(No.2012BAI25B02);Self-selected Subject of China Academyof Chinese Medical Sciences(No.ZZ05003,No.ZZ03090,No.Z0217);the Beijing Key Laboratory of Advanced Information Science and Network Technology(No.XDXX1306)

摘　　要：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.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.

关 键 词：Chinese medicine syndrome classification data mining manifold ranking 

分 类 号：R512.6[医药卫生—内科学]