Researchers have developed a large-scale knowledge graph called LingShu that bridges the gap between traditional Chinese medicine and modern biomedicine. The graph is symptom-centric and contextualized, meaning it takes into account the conditional nature of biomedical knowledge. It integrates data from various sources, including clinical electronic medical records, TCM texts, and biomedical ontologies. The graph's hybrid data model allows for broad connectivity while capturing conditional medical associations. This could lead to better understanding and treatment of diseases. --- Why it matters: This matters to AI researchers because it provides a new approach to representing complex relationships between symptoms, treatments, and diseases in traditional Chinese medicine. The contextualized knowledge graph can be used as a foundation for developing more accurate and personalized diagnosis and treatment systems. Source: https://arxiv.org/abs/2608.20402