| The electronic development of clinical diagnosis and treatment of traditional Chinese medicine has saved a large amount of clinical data and medical ancient books,providing a basis for scholars to study medical knowledge.Although the diagnosis and treatment information is rich today,the utilization of clinical data and medical ancient books is not high.How to use the existing diagnosis and treatment data to obtain the contained medical knowledge more quickly,conveniently and accurately to provide assistance for the future diagnosis and treatment process.Questions to think about.In recent years,scholars’ research on knowledge graphs has fallen into a craze.Knowledge graphs have excellent performance in query-question-answer,graph reasoning and other functions.In this paper,the clinical performance data and traditional Chinese medicine diagnosis and treatment data are used to establish the knowledge map of symptom-disease-prescription-Chinese medicine through the steps of knowledge extraction,knowledge fusion,knowledge processing,etc.Cluster analysis of traditional Chinese medicine,combined with knowledge inference and cluster analysis results in the prototype system of traditional Chinese medicine diagnosis and treatment,provides auxiliary medication decision suggestions.The main work contents of this article include:(1)Aiming at the problem of insufficient utilization of traditional Chinese medical diagnosis and treatment data,constructing a traditional Chinese medical diagnosis and treatment knowledge map based on traditional Chinese medical diagnosis and treatment data and using rule-based reasoning to perform knowledge processing on the traditional Chinese medical diagnosis and treatment knowledge map.The atlas extracts the nodes,attributes,and relationships of traditional Chinese medicines,prescriptions,diseases,and symptoms in "Compendium of Materia Medica" and "Compendium of Typical Chinese Cases" to establish the conceptual relationship of entities.At the same time,extract the instance data information in the TCM diagnosis and treatment data,and then integrate the concept layer node and the instance layer node to establish the relationship between the concept layer node and the instance layer node,and form a more comprehensive TCM diagnosis and treatment knowledge map for knowledge reasoning Inheritance and generalization provide the basis.Finally,rule reasoning is used to establish the relationship between symptoms and prescriptions,symptoms and drugs,which achieves the effect of perfecting the knowledge map of traditional Chinese medicine diagnosis and treatment,and provides better support services for intelligent assistant decision-making.(2)In order to better explore the potential association between traditional Chinese medicine,a clustering algorithm based on the weighted network graph center diffusion method is proposed.The clustering algorithm draws on the idea of Kruskal’s algorithm,and at the same time considers the weight of traditional Chinese medicine in prescriptions,the weight of symptoms in diseases,and the characteristics of its network graph topology,bringing together highly related drugs and diseases.It is helpful to study the regularity of the prescription of traditional Chinese medicine diagnosis and treatment,and provide more scientific recommendations on auxiliary prescriptions.And analyze the results according to the evaluation indicators to ensure the accuracy and effectiveness of the algorithm.(3)Established a prototype system of traditional Chinese medicine diagnosis and treatment.The system contains the rules of prescriptions for clinical diagnosis and treatment of traditional Chinese medicine obtained by weighted network graph center diffusion algorithm,rules for reasoning of clinical knowledge of traditional Chinese medicine,and necessary support environment for operation.It can bring more scientific,standardized and accurate intelligent assistant question and answer experience for clinicians. |
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