Suppr超能文献

使用POSTDOC识别医学院课程文档中的生物医学概念。

Using POSTDOC to recognize biomedical concepts in medical school curricular documents.

作者信息

Kanter S L, Miller R A, Tan M, Schwartz J

机构信息

University of Pittsburgh School of Medicine, Pennsylvania 15261.

出版信息

Bull Med Libr Assoc. 1994 Jul;82(3):283-7.

Abstract

Recognition of the biomedical concepts in a document is prerequisite to further processing of the document: medical educators examine curricular documents to discover the coverage of certain topics, detect unwanted redundancies, integrate new content, and delete old content; and clinicians are concerned with terms in patient medical records for purposes ranging from creation of an electronic medical record to identification of medical literature relevant to a particular case. POSTDOC (POSTprocessor of DOCuments) is a computer application that (1) accepts as input a free-text, ASCII-formatted document and uses the Unified Medical Language System (UMLS) Metathesaurus to recognize relevant main concept terms; (2) provides term co-occurrence data and thus is able to identify potentially increasing correlations among concepts within the document; and (3) retrieves references from MEDLINE files based on user identification of relevant subjects. This paper describes a formative evaluation of POSTDOC's ability to recognize UMLS Metathesaurus biomedical concepts in medical school lecture outlines. The "precision" and "recall" varied over a wide range and were deemed not yet acceptable for automated creation of a database of concepts from curricular documents. However, results were good enough to warrant further study and continued system development.

摘要

识别文档中的生物医学概念是对该文档进行进一步处理的前提条件

医学教育工作者检查课程文档,以发现某些主题的涵盖范围、检测不必要的冗余内容、整合新内容并删除旧内容;而临床医生则关注患者病历中的术语,其目的从创建电子病历到识别与特定病例相关的医学文献不等。POSTDOC(文档后处理器)是一种计算机应用程序,它(1)接受自由文本、ASCII格式的文档作为输入,并使用统一医学语言系统(UMLS)元词表来识别相关的主要概念术语;(2)提供术语共现数据,从而能够识别文档中概念之间潜在的增强相关性;(3)根据用户对相关主题的识别从MEDLINE文件中检索参考文献。本文描述了对POSTDOC在医学院讲座大纲中识别UMLS元词表生物医学概念能力的形成性评估。“精确率”和“召回率”变化范围很广,对于从课程文档自动创建概念数据库而言,被认为尚不可接受。然而,结果足够好,值得进一步研究和持续进行系统开发。

相似文献

2
"Understanding" medical school curriculum content using KnowledgeMap.使用知识图谱“理解”医学院课程内容。
J Am Med Inform Assoc. 2003 Jul-Aug;10(4):351-62. doi: 10.1197/jamia.M1176. Epub 2003 Mar 28.

引用本文的文献

4
"Understanding" medical school curriculum content using KnowledgeMap.使用知识图谱“理解”医学院课程内容。
J Am Med Inform Assoc. 2003 Jul-Aug;10(4):351-62. doi: 10.1197/jamia.M1176. Epub 2003 Mar 28.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验