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《统一医学语言系统的审计技术综述》

A review of auditing techniques for the Unified Medical Language System.

机构信息

Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, New Jersey, USA.

School of Information, Florida State University, Tallahassee, Florida, USA.

出版信息

J Am Med Inform Assoc. 2020 Oct 1;27(10):1625-1638. doi: 10.1093/jamia/ocaa108.

DOI:10.1093/jamia/ocaa108
PMID:32766692
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7566540/
Abstract

OBJECTIVE

The study sought to describe the literature related to the development of methods for auditing the Unified Medical Language System (UMLS), with particular attention to identifying errors and inconsistencies of attributes of the concepts in the UMLS Metathesaurus.

MATERIALS AND METHODS

We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach by searching the MEDLINE database and Google Scholar for studies referencing the UMLS and any of several terms related to auditing, error detection, and quality assurance. A qualitative analysis and summarization of articles that met inclusion criteria were performed.

RESULTS

Eighty-three studies were reviewed in detail. We first categorized techniques based on various aspects including concepts, concept names, and synonymy (n = 37), semantic type assignments (n = 36), hierarchical relationships (n = 24), lateral relationships (n = 12), ontology enrichment (n = 8), and ontology alignment (n = 18). We also categorized the methods according to their level of automation (ie, automated systematic, automated heuristic, or manual) and the type of knowledge used (ie, intrinsic or extrinsic knowledge).

CONCLUSIONS

This study is a comprehensive review of the published methods for auditing the various conceptual aspects of the UMLS. Categorizing the auditing techniques according to the various aspects will enable the curators of the UMLS as well as researchers comprehensive easy access to this wealth of knowledge (eg, for auditing lateral relationships in the UMLS). We also reviewed ontology enrichment and alignment techniques due to their critical use of and impact on the UMLS.

摘要

目的

本研究旨在描述与开发统一医学语言系统(UMLS)审核方法相关的文献,特别关注识别 UMLS 概念词表中概念属性的错误和不一致。

材料与方法

我们应用 PRISMA(系统评价和荟萃分析的首选报告项目)方法,在 MEDLINE 数据库和 Google Scholar 中搜索引用 UMLS 和与审核、错误检测和质量保证相关的若干术语的研究。对符合纳入标准的文章进行定性分析和总结。

结果

详细审查了 83 项研究。我们首先根据各种方面对技术进行分类,包括概念(n=37)、概念名称(n=37)和同义词(n=37)、语义类型分配(n=36)、层次关系(n=24)、横向关系(n=12)、本体丰富(n=8)和本体对齐(n=18)。我们还根据自动化程度(即自动系统、自动启发式或手动)和使用的知识类型(即内在或外在知识)对方法进行分类。

结论

本研究是对 UMLS 各种概念方面审核方法的综合回顾。根据各个方面对审核技术进行分类,将使 UMLS 的维护者以及研究人员能够轻松全面地获取这些知识(例如,用于审核 UMLS 中的横向关系)。我们还回顾了本体丰富和对齐技术,因为它们对 UMLS 的使用和影响至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/25d532ab8891/ocaa108f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/821832173973/ocaa108f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/ee1423d72b22/ocaa108f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/6a69f461c8e7/ocaa108f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/a99db91e2376/ocaa108f4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/25d532ab8891/ocaa108f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/821832173973/ocaa108f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/ee1423d72b22/ocaa108f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/6a69f461c8e7/ocaa108f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/a99db91e2376/ocaa108f4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fecf/7566540/25d532ab8891/ocaa108f5.jpg

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