LingShu knowledge graph bridges Traditional Chinese Medicine and modern biomedicine

Researchers have developed LingShu, a large-scale knowledge graph designed to bridge Traditional Chinese Medicine (TCM) and modern biomedicine. This graph integrates diverse data sources, including clinical records and medical texts, using natural language processing and human verification. LingShu uniquely employs a hybrid data model with both triple and quadruple relations to capture conditional medical associations, such as syndrome-dependent herb efficacy and disease-contextualized drug effects. A web platform is also available for visualization, reasoning, and question-answering. AI

IMPACT This knowledge graph could enhance AI's ability to integrate and reason across different medical knowledge systems.

RANK_REASON The cluster contains an academic paper detailing a new knowledge graph. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• interactive machine learning
• Modern Biomedicine
• natural language processing
• traditional Chinese medicine

• paper
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →