摘要
【目的】对PubMed收录的高证据疾病文献进行挖掘与知识发现,为疾病临床诊疗和日常防控提供借鉴。【方法】利用语义抽取工具SemRep,提出基于SPO语义三元组的疾病知识发现模型,选取糖尿病相关文献对模型进行验证,结合可视化及临床知识进行糖尿病知识发现。【结果】获得糖尿病SPO三元组1 258个,语义关系16个,揭示了糖尿病相关的基因、常见的并发症、检测手段及治疗方式。【局限】数据来源为公开发表的文献,未从知识库、电子病历等真实世界数据发现疾病知识。【结论】验证了基于SPO语义三元组的疾病知识发现模型用于揭示大规模文献中隐含的生物医学知识的可行性,有助于为生物医学科研人员提供潜在的研究假设和思路参考。
[Objective] This study tries to discover knowledge from the high-level evidence-based literature on diseases indexed by PubMed, aiming to provide reference for clinical diagnosis, treatment, as well as routine prevention and control of diseases. [Methods] We proposed a diseases knowledge discovery model based on SPO predications with the semantic extraction tool SemRep. Then we selected the diabetes-related literature to evaluate this model, and discovered knowledge based on SPO visualization and clinical knowledge. [Results] We obtained1 258 SPO predications and 16 semantic relationships, which identified diabetes-related genes, common complications, as well as detection and treatment methods. [Limitations] We only examined our model with publicly accessible literature. More research is needed to include knowledge bases and electronic medical records.[Conclusions] The disease knowledge discovery model based on SPO predication could identify the biomedical knowledge from literature, which provides potential research hypotheses and ideas for biomedical researchers.
作者
蔡妙芝
李晓瑛
赵嘉玮
冯凤翔
任慧玲
Cai Miaozhi;Li Xiaoying;Zhao Jiawei;Feng Fengxiang;Ren Huiling(Institute of Medical Information,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100020,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2022年第1期134-144,共11页
Data Analysis and Knowledge Discovery
基金
科技创新2030-“新一代人工智能”重大项目课题(项目编号:2019AAA0104901)
国家社会科学基金项目(项目编号:20BTQ062)
中国WHO双年合作项目(项目编号:GJ2-2021-WHOSO-01)的研究成果之一。
关键词
SPO
糖尿病
知识发现
知识组织
SPO
Diabetes Mellitus
Knowledge Discovery
Knowledge Organization
