Kanter S L, Miller R A, Tan M, Schwartz J
University of Pittsburgh School of Medicine, Pennsylvania 15261.
Bull Med Libr Assoc. 1994 Jul;82(3):283-7.
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.
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。
