Automatic detection of negated findings with nooj: First results

The objective of this study is to develop a methodology for the automatic detection of negated findings in radiological reports which takes into account semantic and syntactic descriptions, as well as morphological and syntactic analysis rules. In order to achieve this goal, a series of rules for pr...

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Guardado en:
Detalles Bibliográficos
Publicado: 2018
Materias:
Negated finding
NooJ
Syntactic rules
Information systems
Information use
Semantics
Syntactics
Terminology
Computational framework
Electronic dictionaries
Grammatical information
Medical terminologies
Syntactic information
Natural language processing systems
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v10859LNCS_n_p298_Koza
http://hdl.handle.net/20.500.12110/paper_03029743_v10859LNCS_n_p298_Koza
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_03029743_v10859LNCS_n_p298_Koza
record_format dspace
spelling paper:paper_03029743_v10859LNCS_n_p298_Koza2023-06-08T15:28:16Z Automatic detection of negated findings with nooj: First results Negated finding NooJ Syntactic rules Information systems Information use Semantics Syntactics Terminology Computational framework Electronic dictionaries Grammatical information Medical terminologies Negated finding NooJ Syntactic information Syntactic rules Natural language processing systems The objective of this study is to develop a methodology for the automatic detection of negated findings in radiological reports which takes into account semantic and syntactic descriptions, as well as morphological and syntactic analysis rules. 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 computerized grammar. Computational framework was carried out with NooJ, a free software developed by Silberztein, which has various utilities for treating natural language. Results show that the detection of negated findings improves if lexical-grammatical information is added. © 2018, Springer International Publishing AG, part of Springer Nature. 2018 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v10859LNCS_n_p298_Koza http://hdl.handle.net/20.500.12110/paper_03029743_v10859LNCS_n_p298_Koza
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Negated finding
NooJ
Syntactic rules
Information systems
Information use
Semantics
Syntactics
Terminology
Computational framework
Electronic dictionaries
Grammatical information
Medical terminologies
Negated finding
NooJ
Syntactic information
Syntactic rules
Natural language processing systems
spellingShingle Negated finding
NooJ
Syntactic rules
Information systems
Information use
Semantics
Syntactics
Terminology
Computational framework
Electronic dictionaries
Grammatical information
Medical terminologies
Negated finding
NooJ
Syntactic information
Syntactic rules
Natural language processing systems
Automatic detection of negated findings with nooj: First results
topic_facet Negated finding
NooJ
Syntactic rules
Information systems
Information use
Semantics
Syntactics
Terminology
Computational framework
Electronic dictionaries
Grammatical information
Medical terminologies
Negated finding
NooJ
Syntactic information
Syntactic rules
Natural language processing systems
description The objective of this study is to develop a methodology for the automatic detection of negated findings in radiological reports which takes into account semantic and syntactic descriptions, as well as morphological and syntactic analysis rules. 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 computerized grammar. Computational framework was carried out with NooJ, a free software developed by Silberztein, which has various utilities for treating natural language. Results show that the detection of negated findings improves if lexical-grammatical information is added. © 2018, Springer International Publishing AG, part of Springer Nature.
title Automatic detection of negated findings with nooj: First results
title_short Automatic detection of negated findings with nooj: First results
title_full Automatic detection of negated findings with nooj: First results
title_fullStr Automatic detection of negated findings with nooj: First results
title_full_unstemmed Automatic detection of negated findings with nooj: First results
title_sort automatic detection of negated findings with nooj: first results
publishDate 2018
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v10859LNCS_n_p298_Koza
http://hdl.handle.net/20.500.12110/paper_03029743_v10859LNCS_n_p298_Koza
_version_ 1768545328036839424

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