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Automatic Detection of Negated Findings in Radiological Reports for Spanish Language: Methodology Based on Lexicon-Grammatical Information Processing

  • Walter Koza
  • Darío Filippo
  • Viviana Cotik
  • Vanesa Stricker
  • Mirian Muñoz
  • Ninoska Godoy
  • Natalia Rivas
  • Ricardo Martínez-Gamboa
Article

Abstract

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.

Keywords

Negated findings Automatic recognition Lexicon-grammar NooJ NegEx 

Notes

Funding Information

This research was supported by a grant from the Proyecto Fondecyt Regular 1171033, from the Comisión Nacional de Investigación Científica y Tecnológica (Conicyt), Chile.

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Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  1. 1.Instituto de Literatura y Ciencias del LenguajePontificia Universidad Católica de ValparaísoValparaísoChile
  2. 2.Hospital Pediátrico GarrahanBuenos AiresArgentina
  3. 3.Departamento de Ciencias de la Computación, FCEyNUniversidad de Buenos AiresBuenos AiresArgentina
  4. 4.Universidad Diego PortalesSantiagoChile

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