摘要
目的应用贝叶斯网络学习算法预测中药活血化瘀功效。方法在中医药理论的指导下,利用贝叶斯网络学习算法,研究了55味常用中药的活血化瘀功效与9个药理指标之间的关联关系,得到贝叶斯网络结构和条件概率表。结果利用建立的贝叶斯网络功效与药理的关系模型进行数据分析,预测了中药有活血化瘀功效的概率值。结论贝叶斯网络可用于中药或中药组分功效的预测,为发现中药功效研究提供了一种新的思路。
Objective To predict the effects of Chinese herbal medicine（CHM） with the actions of blood-activating and stasis-eliminating by the application of Bayesian belief noework （BBN）. Method The connective relation between 55 kinds of CHM with the actions of blood-activating and stasis-eliminating and 9 pharmacologic indexes was studied by using BBN learning algorithm under the guide of TCM theory. The structure and conditional probability tables of BBN were obtained. Results The model of relationship between BBN effect and pharmacology was applied to analyze on data and probability value of CHM with the effects of blood-activating and stasis-eliminating was predicted. Conclusion Bayesian network method can be used to predict the effects of CHM and their components. The study provided a new technical evidence for the research of CHM effects.
出处
《北京中医药大学学报》
CAS
CSCD
北大核心
2008年第4期229-231,共3页
Journal of Beijing University of Traditional Chinese Medicine
基金
国家重点基础研究发展计划(973计划)资助项目(No.2005CB523401
No.2006CB504703)
关键词
贝叶斯网络
活血化瘀
数据挖掘
Bayesian belief network
blood-activating and stasis-eliminating
data mining
