Objective To design and construct a syndrome differentiation knowledge graph that integrates TCM facial color diagnosis information;To explore the hidden relationships between the knowledge.Methods The literature data came from ancient classics,textbooks,as well as standard literature related to inspection included in the CNKI,VIP and Wanfang Data from the establishment of the databases to December 31,2022.The clinical data was sourced from 30 elderly individuals who underwent TCM health examinations at the Community Health Service Center in Jiading Industrial Zone,Shanghai in September 2022.Facial image acquisition was performed using TFDA-1 digital tongue and facial diagnostic instrument.By following the steps of knowledge extraction,knowledge fusion and quality assessment to construct a graph,and with the assistance of TCM experts for interpretation,using Access 2019 to integrate qualitative textual data and quantitative objective image digital information,a syndrome differentiation knowledge graph integrating TCM facial diagnosis was designed and completed in the Neo4j graph database.In addition,a method was designed to shift facial diagnosis knowledge from qualitative to quantitative.Results There were a total of 194 nodes under 8 entity term types and 12 entity term labels,as well as 361 relationships under 13 semantic relationships in knowledge graph.The Neo4j graph database provided a visualized TCM facial color diagnosis and differentiation,which could be queried and fed back using Cypher language.Conclusion The knowledge graph constructed based on the theory of TCM facial color diagnosis visually shows the complex correlation between facial color diagnosis and syndrome differentiation diagnosis,with a knowledge representation model that forms qualitative data of image features → semantic relationships → syndrome differentiation diagnosis forms.