山东中医杂志2024，Vol.43Issue(7)：670-674,728,6.DOI:10.16295/j.cnki.0257-358x.2024.07.002
动态不确定因果图在中医诊断中的应用探讨
Discussion on Application of Dynamic Uncertain Causal Graph in Traditional Chinese Medicine Diagnosis
摘要
Abstract
Dynamic uncertainty causality graph(DUCG)has emerged as an advanced knowledge representation and reasoning model in the field of traditional Chinese medicine(TCM).In order to better use DUCG to provide diagnostic reasoning and decision-making support for TCM in clinic,in this paper the main problems of DUCG in TCM diagnosis at this stage were discussed,based on summarizing the research and application of DUCG in TCM field including the unification of TCM terminology standardization and the quality of TCM knowledge base,the selection and design of inference algorithms and model construction methods,and the platformization and productization of DUCG TCM diagnostic models.According to the problems,the application ideas and methods were discussed and it was put forwards that the technical connotation of DUCG should be deeply excavated,precise and efficient inference modeling methods should be selected according to the actual clinical needs,intelli-gent auxiliary diagnostic models consistent with the theoretical ideas of TCM and with the characteristics of TCM should be built,and the development and application of DUCG collaborative research platforms and products should be strengthened.关键词
中医诊断/动态不确定因果图/人工智能/应用方法/辅助诊疗Key words
traditional Chinese medicine diagnosis/dynamic uncertain causal graph/artificial intelligence/appli-cation methods/auxiliary diagnosis分类
医药卫生引用本文复制引用
李敏,戴国华,高武霖..动态不确定因果图在中医诊断中的应用探讨[J].山东中医杂志,2024,43(7):670-674,728,6.基金项目
国家重点研发计划项目(编号:2019YFC1710401) （编号:2019YFC1710401）
国家自然科学基金项目(编号:81774047) （编号:81774047）
