Automatic Detection of Negated Findings in Radiological Reports for Spanish Language: Methodology Based on Lexicon-Grammatical Information Processing
| Autor: | Ninoska Godoy, Darío Filippo, Mirian Muñoz, Vanesa Stricker, Ricardo Martínez-Gamboa, Walter Koza, Viviana Cotik, Natalia Rivas |
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| Rok vydání: | 2018 |
| Předmět: |
Medical terminology
Computer science media_common.quotation_subject Lexicon computer.software_genre Article 030218 nuclear medicine & medical imaging 03 medical and health sciences Specialized dictionary 0302 clinical medicine Rule-based machine translation Electronic dictionary Terminology as Topic Electronic Health Records Humans Radiology Nuclear Medicine and imaging Language media_common Electronic Data Processing SNOMED CT Radiological and Ultrasound Technology Grammar business.industry Linguistics Computer Science Applications Artificial intelligence Radiology business computer 030217 neurology & neurosurgery Natural language processing Natural language |
| Zdroj: | Journal of Digital Imaging. 32:19-29 |
| ISSN: | 1618-727X 0897-1889 |
| DOI: | 10.1007/s10278-018-0113-8 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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