期刊论文

Syndrome differentiation system of traditional Chinese medicine based on Bayesian network

Zhu, Y.-H.

中文

湖南大学学报. 自然科学版

Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences

1000-2472

2006

33

4

123-125

10.3321/j.issn:1000-2472.2006.04.028

国家重点基础研究发展（973）计划（2003CB517101）；

本校为其他机构

将贝叶斯网络运用于中医辨证系统的研究，以更加量化中医辨证诊断系统．通过将中医体系中的916个证候，51项证素及其构成的1700条证名构成中医辨证贝叶斯网络的节点集，初步建立起中医辨证数据库并通过网络学习，形成中医辨证贝叶斯网络结构及概率表．利用建立的贝叶斯网络中医辨证系统，进行数据计量分析、推理验证证候-证素-证名间的关系，其结果与中医专家经验有很高的吻合性，尽管其仍未能全面反映中医辨证的思维能力．所以贝叶斯网络是对中医辨证进行信息挖掘处理的一种较好方法，可应用于中医人工智能辨证系统的建立．

This paper applied Bayesian network to the syndrome differentiation research to improve the quantification of syndrome differentiation diagnosis system in traditional Chinese medicine (TCM). 916 syndromes, 51 key pattern elements and 1700 syndrome names as nodes collection of Bayesian network were selected for the database, and the framework and probability table for the Bayesian network of TCM syndrome differentiation were made through the network learning. Then, the constructed system was applied to explore the relationship among the syndrome, the key pattern elements and the syndrome names....