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

LingShu知识图谱连接中医药与现代生物医学

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了LingShu，一个旨在连接中医药（TCM）与现代生物医学的大规模知识图谱。该图谱整合了包括临床记录和医学文本在内的多样化数据源，并利用自然语言处理和人工验证。LingShu独特地采用了混合数据模型，包含三元组和四元组关系，以捕捉条件性医学关联，例如证候依赖的草药疗效和疾病情境化的药物作用。同时提供了一个用于可视化、推理和问答的网络平台。 AI

影响 该知识图谱可以增强AI在不同医学知识系统之间进行整合和推理的能力。

排序理由 该集群包含一篇详细介绍新知识图谱的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LingShu知识图谱连接中医药与现代生物医学

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该集群包含一篇详细介绍新知识图谱的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [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：一个大规模以症状为中心的语境化知识图谱，连接中医药与现代生物医学

    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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