[1]孙 淼,王家欣,许建成.大数据视域下检验医学知识图谱的临床应用与评价[J].现代检验医学杂志,2025,40(05):200-204.[doi:10.3969/j.issn.1671-7414.2025.05.038]
　SUN Miao,WANG Jiaxin,XU Jiancheng.Clinical Application and Evaluation of Knowledge Graphs in Laboratory Medicine from the Perspective of Big Data[J].Journal of Modern Laboratory Medicine,2025,40(05):200-204.[doi:10.3969/j.issn.1671-7414.2025.05.038]
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大数据视域下检验医学知识图谱的临床应用与评价()

《现代检验医学杂志》[ISSN:/CN:]

卷:
第40卷
期数:
2025年05期
页码:
200-204
栏目:
综述
出版日期:
2025-09-15

文章信息/Info

Title:
Clinical Application and Evaluation of Knowledge Graphs in Laboratory Medicine from the Perspective of Big Data
文章编号:
1671-7414（2025）05-200-05
作者:
孙 淼，王家欣，许建成
吉林大学第一医院检验科，长春 130021
Author(s):
SUN Miao，WANG Jiaxin，XU Jiancheng
Department of Clinical Laboratory，the First Hospital of Jilin University, Changchun 130021, China
关键词:
检验医学; 知识图谱; 大数据; 实验室检查
分类号:
R446
DOI:
10.3969/j.issn.1671-7414.2025.05.038
文献标志码:
A
摘要:
近年，大数据分析技术推动知识图谱在医学领域中的应用，检验医学作为支持临床决策的重要基础，汇集了大量反映患者生理指标的数据。知识图谱可挖掘检验数据中的隐藏价值，提供精确的检验信息。现阶段，检验医学知识图谱可发掘检测项目间关系并辅助诊断，整合患者实验室检查历史趋势，预测药物不良反应。文章从检验项目间关系、辅助诊断、用药指导三个方面分析和评价知识图谱在检验医学中的应用。进一步提出扩展检验医学知识图谱在语义搜索、决策支持以及智能问答等方面的发展，推动临床检验诊断智能化建设。
Abstract:
Knowledge graphs have been more popular in the medical industry in recent years due to the development of big data analysis technologies. Information reflecting a range of physiological markers of patients is gathered in laboratory medicine, which forms an essential basis for clinical decision-making. Knowledge graphs could uncover the hidden value in inspection and consequently furnish accurate inspection data. Knowledge graphs are currently used in laboratory medicine to forecast possible adverse drug responses, help with diagnosis, integrate historical trends of patient laboratory inspections, and identify correlations across detection projects. The interaction between inspection items, auxiliary diagnosis, and medication guidance are three angles from which the use of knowledge graphs in laboratory medicine is analyzed and evaluated. Further support the intelligent construction of clinical laboratory diagnosis, it is also suggested that the development of test medical knowledge graphs extend in the direction of semantic search, decision support, and intelligent question answer.

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备注/Memo

备注/Memo:
基金项目：吉林省科技发展计划项目（20220401085YY）。
作者简介：孙淼（2000-），女，硕士在读，主要研究方向：大数据分析及分子生物学检测，E-mail：sunmiaom2000@163.com。
通讯作者：许建成（1976-），男，教授，博士生导师，主任医师，主要从事临床检验诊断工作，E-mail：xjc@jiu.edu.com。
更新日期/Last Update: 2025-09-15