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LingShu knowledge graph bridges Traditional Chinese Medicine and modern biomedicine

By PulseAugur Editorial · [1 sources] ·

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 →

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

LingShu knowledge graph bridges Traditional Chinese Medicine and modern biomedicine

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

  1. arXiv cs.AI TIER_1 English(EN) · 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

    arXiv:2608.20402v1 Announce Type: cross Abstract: Biomedical knowledge graphs (KGs) are pivotal for knowledge organization, yet traditional binary relations often struggle to represent the conditional nature of biomedical knowledge. Symptoms provide a shared phenotypic layer for …

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