A Semantic Knowledge Graph Linking Diseases, Patterns, Symptoms, and Herbs for Traditional Chinese Medicine
Yuanbai Li
Zenodo (CERN European Organization for Nuclear Research)
Problems Identified (2)
TCM efficacy knowledge representation: Simple efficacy lists are insufficient for representing the full semantic clinical reasoning structure of Traditional Chinese Medicine efficacy knowledge.
TCM efficacy knowledge representation: Simple efficacy lists are insufficient for representing the full semantic clinical reasoning structure of Traditional Chinese Medicine efficacy knowledge.
Proposed Solutions (2)
TCM semantic efficacy knowledge graph: A property-graph dataset constructs a semantic TCM efficacy knowledge graph integrating etiologies, diseases, patterns, symptoms, efficacies, and herbs with standardized entities and relationships.
TCM semantic efficacy knowledge graph: A property-graph dataset constructs a semantic TCM efficacy knowledge graph integrating etiologies, diseases, patterns, symptoms, efficacies, and herbs with standardized entities and relationships.
Results (3)
TCM graph dataset released:
Graph scale:
Reasoning-ready graph structure:
Research Domain
Traditional Chinese Medicine knowledge graphs