Article type
Abstract
"Background
The transformation and application of the clinical practice guidelines for Integrated traditional Chinese and Western medicine (TCM and WM CPGs) is a crucial link in the transformation of achievements of medical science and technology. However, there are many problems with the operability of the current TCM and WM CPGs in clinical decision-making and practice.
Objectives
The introduction of knowledge graph technology provides a solid foundation for TCM and WM CPGs intelligence and a good tool for solving guideline implementation problems.
Methods
The framework of knowledge graph was designed based on TCM and WM CPGs.
Results
Using the current status of disease diagnosis and treatment and the current problems in the application of TCM and WM CPGs, we defined the objectives of constructing a knowledge graph for TCM and WM CPGs, and accordingly designed a knowledge graph framework for TCM and WM CPGs that is consistent with professional knowledge and practical application. We analyzed the scope of the TCM and WM CPGs, arranged their content and summarized their knowledge structure. Concept structure tables and entity semantic relationship tables were established. We then extracted entities and relationships from the TCM and WM CPGs, sorted them into the entity database and triple relationship databases for knowledge importation, used Neo4j for knowledge storage, retrieved and verified the correctness of the knowledge graph, and completed the visual display. Experts were invited to evaluate the scientific nature and methodological effectiveness of the knowledge graph.
Discussions
The design of the knowledge graph construction framework based on the TCM and WM CPGs provides an interpretable basis for the recommendation results of clinical decision support system, which is conducive to the implementation and dissemination of the CPGs."
The transformation and application of the clinical practice guidelines for Integrated traditional Chinese and Western medicine (TCM and WM CPGs) is a crucial link in the transformation of achievements of medical science and technology. However, there are many problems with the operability of the current TCM and WM CPGs in clinical decision-making and practice.
Objectives
The introduction of knowledge graph technology provides a solid foundation for TCM and WM CPGs intelligence and a good tool for solving guideline implementation problems.
Methods
The framework of knowledge graph was designed based on TCM and WM CPGs.
Results
Using the current status of disease diagnosis and treatment and the current problems in the application of TCM and WM CPGs, we defined the objectives of constructing a knowledge graph for TCM and WM CPGs, and accordingly designed a knowledge graph framework for TCM and WM CPGs that is consistent with professional knowledge and practical application. We analyzed the scope of the TCM and WM CPGs, arranged their content and summarized their knowledge structure. Concept structure tables and entity semantic relationship tables were established. We then extracted entities and relationships from the TCM and WM CPGs, sorted them into the entity database and triple relationship databases for knowledge importation, used Neo4j for knowledge storage, retrieved and verified the correctness of the knowledge graph, and completed the visual display. Experts were invited to evaluate the scientific nature and methodological effectiveness of the knowledge graph.
Discussions
The design of the knowledge graph construction framework based on the TCM and WM CPGs provides an interpretable basis for the recommendation results of clinical decision support system, which is conducive to the implementation and dissemination of the CPGs."