There are many shortcomings in the readability and applicability of current clinical practice guidelines used both in the computer-aided clinical decision making process and in clinical practice. We have explored the framework of the universality of guidelines by standardizing the representation of their structure and knowledge; and the relationship between this and the guideline knowledge. Promoting the standardization and standardized expression of guideline knowledge and constructing a standardized easily shareable guideline knowledge base that is transplantable through modeling and demonstration, is conducive to meeting the needs for the development of a clinical decision support system promoting the implementation of clinical practice guidelines and the improvement of clinical diagnosis and treatment service quality. The introduction of knowledge graphs provides a solid foundation for digital intelligentization of guidelines. However, there is little methodological content available for guideline knowledge graph construction. This study used the construction of a knowledge graph for Evidence-based clinical practice guidelines for the treatment and monitoring of non-muscular invasive bladder cancer in China (2018 Standard Edition) as an example. We identified the guideline module, analyzed its basic information, background and the scope of its methodological content, then set out the hierarchical relationship between concepts in combination with expert opinions, designed the concept structure table according to multi-level concept layers and concept examples, adjusted the relationship structure between concepts, and improved the relationship between the different entities. This article discusses and summarizes the modeling and representation methods of the basic information, background and methods of the guidelines, thus providing a reference for the construction of knowledge maps for other clinical practice guidelines in the future. 

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