基于 LIS 的检测知识图谱构建系统

Fengyang Fu, Shuangling Sun, Yi Liu
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引用次数: 0

摘要

为了弥补医学检验领域基于实验室信息系统(LIS)真实实验数据的知识图谱的不足,提出了一种基于实验室信息系统的医学检验知识图谱构建方法和系统。通过建立数据库和推理机等工具,解决了如何从现实世界中获取丰富、准确的医学专业文献资源的问题。以大量临床检验标本为数据源,利用数据挖掘技术对海量信息进行分析处理,从而生成高质量的可视化医学检验知识图谱。医生首先要为患者做一些诊前准备,然后进行全面系统的体格检查。通过构建医学检验知识图谱,我们为 LIS 系统的应用场景带来了新的可能性。
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LIS-based Inspection Knowledge Graph Construction System
In order to fill the lack of knowledge graph based on real experimental data from Laboratory Information System (LIS) in the field of medical testing, a method and system for constructing medical testing knowledge graph based on LIS is proposed. The problem of how to obtain rich and accurate literature resources of medical specialty from the real world is solved by building a database and tools such as reasoning machine. Using a large number of clinical laboratory specimens as a data source, data mining technology is used to analyze and process the massive information, so as to generate a high-quality visualization of the medical test knowledge graph. Doctors first do some pre-diagnostic preparations for patients, and then conduct a comprehensive and systematic physical examination. By building a medical test knowledge map, we have brought new possibilities for the application scenarios of LIS system.
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