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首页> 外文期刊>Journal of digital imaging: the official journal of the Society for Computer Applications in Radiology >Automatic Detection of Negated Findings in Radiological Reports for Spanish Language: Methodology Based on Lexicon-Grammatical Information Processing
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Automatic Detection of Negated Findings in Radiological Reports for Spanish Language: Methodology Based on Lexicon-Grammatical Information Processing

机译：自动检测西班牙语语言放射报告中的否定结果：基于词典语法信息处理的方法

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摘要

We present a methodology for the automatic recognition of negated findings in radiological reports considering morphological, syntactic, and semantic information. In order to achieve this goal, a series of rules for processing lexical and syntactic information was elaborated. This required development of an electronic dictionary of medical terminology and informatics grammars. Pertinent information for the assembly of the specialized dictionary was extracted from the ontology SNOMED CT and a medical dictionary (RANM, 2012). Likewise, a general language dictionary was also included. Lexicon-Grammar (LG), proposed by Gross (1975; Cahiers de l'institut de linguistique de Louvain, 24. 23-41 1998), was used to set up the database, which allowed an exhaustive description of the argument structure of predicates projected by lexical units. Computational framework was carried out with NooJ, a free software developed by Silberztein (Silberztein and Noo 2018, 2016), which has various utilities for treating natural language, such as morphological and syntactic grammar, as well as dictionaries. This methodology was compared with a Spanish version of NegEx (Chapman et al. Journal of Biomedical Informatics, 34(5):301-310 2001; Stricker 2016). Results show that there are minimal differences in favor of the algorithm developed using NooJ, but the quality and specificity of the data improves if lexical-grammatical information is added.
机译：考虑到形态，句法和语义信息，我们提出了一种自动识别否定发现的否定结果。为了实现这一目标，详细阐述了一系列处理词法和句法信息的规则。这需要发展电子术语和信息学语法的电子词典。从本体上的CT和医学词典中提取了专门词典的组装的相关信息（RANM，2012）。同样，还包括一般语言词典。由Gross（1975年）提出的Lexicon-Grammar（LG）（1975; Cahiers de L'Institut de Lueistique，24.23-41 1998），用于设置数据库，该数据库允许详尽的谓词结构描述由词汇单位预测。计算框架与Nooj进行了一款由Silberztein（Silberztein和Noo 2018,2016）开发的自由软件，该软件具有各种用于治疗自然语言的公用事业，例如形态和句法语法，以及词典。将该方法与西班牙语版的Negex（Chapman等人）进行比较（生物医学信息学杂志，34（5）：301-310 2001; Stricker 2016）。结果表明，使用NOOJ开发的算法存在最小差异，但数据的质量和特异性提高了如果添加了词汇语法信息。

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