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arXiv AI By Rui Hua, Zixin Shu, Kai Chang, Dengying Yan, Jianan Xia, Hui Zhu, Shujie Song, Shurui Yang, Tongxin Wang, Yue Yin, Yu Wei, Lijuan Pei, Yunhui Hu, Hao Xu, Mingzhong Xiao, Xiaodong Li, Haibin Yu, Runshun Zhang, Wenjia Wang, Baoyan Liu, Xuezhong Zhou

LingShu: A Large-Scale Symptom-Centric Contextualized Knowledge Graph Bridging Traditional Chinese Medicine and Modern Biomedicine

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LingShu is a large-scale, symptom‑centric knowledge graph that bridges Traditional Chinese Medicine (TCM) and modern biomedicine. It contains 17.33 million entity records and 39.47 million relation records, combining 17.19 million semantic triples with 22.29 million contextualized quadruples to encode conditional medical associations. The graph integrates data from electronic medical records, TCM texts, biomedical ontologies, and curated knowledge bases, and is supported by a web platform offering visualization, reasoning, and evidence‑grounded question answering.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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