Clinical Application and Evaluation of Knowledge Graphs in Laboratory Medicine from the Perspective of Big Data
10.3969/j.issn.1671-7414.2025.05.038
- VernacularTitle:大数据视域下检验医学知识图谱的临床应用与评价
- Author:
Miao SUN
1
;
Jiaxin WANG
1
;
Jiancheng XU
1
Author Information
1. 吉林大学第一医院检验科,长春 130021
- Publication Type:Journal Article
- Keywords:
laboratory medicine;
knowledge graphs;
big data;
laboratory examination
- From:
Journal of Modern Laboratory Medicine
2025;40(5):200-204
- CountryChina
- Language:Chinese
-
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.
