基于贝叶斯网络评价中医药疗效思路与方法  

Approaches to Efficacy Evaluation of Chinese Medicine by Bayesian Networks

作　　者：甘叶娜 李多多[1] 梁少伟 陈可冀[3] 刘建平[4] GAN Ye-na;LI Duo-duo;LIANG Shao-wei;CHEN Ke-ji;LIU Jian-ping(Department of Tuina and Pain,Dongzhimen Hospital,Beijing University of Chinese Medicine,Bejing,100700;Shenzhen Institute of Artificial Intelligence and Robotics for Society,Shenzhen,518129;Department of Cardiology,Xiyuan Hospital,China Academy of Chinese Medical Sciences,Beijing,100091;Centre for Evidence-Based Chinese Medicine,Bejing University of Chinese Medicine,Beijing,100029)

机构地区：[1]北京中医药大学东直门医院推拿疼痛科,北京100700 [2]深圳市人工智能与机器人研究院,深圳518129 [3]中国中医科学院西苑医院心血管病中心,北京100091 [4]北京中医药大学循证医学中心,北京100029

出　　处：《中国中西医结合杂志》2024年第4期486-491,共6页Chinese Journal of Integrated Traditional and Western Medicine

基　　金：国家自然科学基金重点项目(No.81830115)。

摘　　要：中医药疗效评价研究是推动中医药现代化、国际化发展的重要内容,但通过现有疗效评价方法常难以表示和呈现真实世界研究证据间潜在的因果关联。贝叶斯网络可利用网络来解析场景中潜在的因果关联,并对其进行动态更新,若能运用此方法来表示和呈现中医药诊疗研究证据,将有望从因果关联视角更清晰地了解、说明和评价中医药临床疗效的研究证据。The evaluation of efficacy in Chinese medicine(CM)research is an important aspect for promoting the modernization and internationalization of CM.However,existing methods of efficacy evaluation often struggle to represent and present the potential causal relationships among real-world research evidence.Bayesian networks can utilize a network to analyze the underlying causal relationships in a given scenario and dynamically update them.If this method could be applied to represent and present the evidence of CM diagnosis and treatment research,it may offer a clearer understanding,explanation,and evaluation of the clinical efficacy of CM from a causal relationship perspective.

关 键 词：中医药 疗效评价 贝叶斯网络 临床研究方法 真实世界研究 证据 

分 类 号：O212.8[理学—概率论与数理统计] R24[理学—数学]