USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES

Detalhes bibliográficos
Autor(a) principal: Gomes,Denilsen Carvalho
Data de Publicação: 2019
Outros Autores: Oliveira,Lucas Emanuel Silva e, Cubas,Marcia Regina, Barra,Claudia Maria Cabral Moro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Texto & contexto enfermagem (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-07072019000100601
Resumo: ABSTRACT Objective: to reflect on the use of computational tools in the cross-mapping method between clinical terminologies. Method: reflection study. Results: the cross-mapping method consists of obtaining a list of terms through extraction and normalization; the connection between the terms of the list and those of the reference base, by means of predefined rules; and grouping of the terms into categories: exact or partial combination or, in more detail, similar term, more comprehensive term, more restricted term and non-agreeing term. Performed manually in many studies, it can be automated with the use of the Unified Medical Language System (UMLS). Obtaining the terms list can occur automatically by natural language processing algorithms, being that the use of rules to identify information in texts allows the expert's knowledge to be coupled to the algorithm, and it can be performed by techniques based on Machine Learning. When it comes to mapping terms using the 7-Axis model of the International Classification for Nursing Practice (ICNP®), the process can also be automated through natural language processing algorithms such as POS-tagger and the syntactic parser. Conclusion: the cross-mapping method can be intensified by the use of natural language processing algorithms. However, even in cases of automatic mapping, the validation of the results by specialists should not be discarded.
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spelling USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIESTerminologyNursingInformaticsControlled vocabularyMethodsABSTRACT Objective: to reflect on the use of computational tools in the cross-mapping method between clinical terminologies. Method: reflection study. Results: the cross-mapping method consists of obtaining a list of terms through extraction and normalization; the connection between the terms of the list and those of the reference base, by means of predefined rules; and grouping of the terms into categories: exact or partial combination or, in more detail, similar term, more comprehensive term, more restricted term and non-agreeing term. Performed manually in many studies, it can be automated with the use of the Unified Medical Language System (UMLS). Obtaining the terms list can occur automatically by natural language processing algorithms, being that the use of rules to identify information in texts allows the expert's knowledge to be coupled to the algorithm, and it can be performed by techniques based on Machine Learning. When it comes to mapping terms using the 7-Axis model of the International Classification for Nursing Practice (ICNP®), the process can also be automated through natural language processing algorithms such as POS-tagger and the syntactic parser. Conclusion: the cross-mapping method can be intensified by the use of natural language processing algorithms. However, even in cases of automatic mapping, the validation of the results by specialists should not be discarded.Universidade Federal de Santa Catarina, Programa de Pós Graduação em Enfermagem2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-07072019000100601Texto & Contexto - Enfermagem v.28 2019reponame:Texto & contexto enfermagem (Online)instname:Universidade Federal de Santa Catarina (UFSC)instacron:UFSC10.1590/1980-265x-tce-2017-0187info:eu-repo/semantics/openAccessGomes,Denilsen CarvalhoOliveira,Lucas Emanuel Silva eCubas,Marcia ReginaBarra,Claudia Maria Cabral Moroeng2019-03-22T00:00:00Zoai:scielo:S0104-07072019000100601Revistahttp://www.scielo.br/tcePUBhttps://old.scielo.br/oai/scielo-oai.phptextoecontexto@nfr.ufsc.br1980-265X0104-0707opendoar:2019-03-22T00:00Texto & contexto enfermagem (Online) - Universidade Federal de Santa Catarina (UFSC)false
dc.title.none.fl_str_mv USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
title USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
spellingShingle USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
Gomes,Denilsen Carvalho
Terminology
Nursing
Informatics
Controlled vocabulary
Methods
title_short USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
title_full USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
title_fullStr USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
title_full_unstemmed USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
title_sort USE OF COMPUTATIONAL TOOLS AS SUPPORT TO THE CROSS-MAPPING METHOD BETWEEN CLINICAL TERMINOLOGIES
author Gomes,Denilsen Carvalho
author_facet Gomes,Denilsen Carvalho
Oliveira,Lucas Emanuel Silva e
Cubas,Marcia Regina
Barra,Claudia Maria Cabral Moro
author_role author
author2 Oliveira,Lucas Emanuel Silva e
Cubas,Marcia Regina
Barra,Claudia Maria Cabral Moro
author2_role author
author
author
dc.contributor.author.fl_str_mv Gomes,Denilsen Carvalho
Oliveira,Lucas Emanuel Silva e
Cubas,Marcia Regina
Barra,Claudia Maria Cabral Moro
dc.subject.por.fl_str_mv Terminology
Nursing
Informatics
Controlled vocabulary
Methods
topic Terminology
Nursing
Informatics
Controlled vocabulary
Methods
description ABSTRACT Objective: to reflect on the use of computational tools in the cross-mapping method between clinical terminologies. Method: reflection study. Results: the cross-mapping method consists of obtaining a list of terms through extraction and normalization; the connection between the terms of the list and those of the reference base, by means of predefined rules; and grouping of the terms into categories: exact or partial combination or, in more detail, similar term, more comprehensive term, more restricted term and non-agreeing term. Performed manually in many studies, it can be automated with the use of the Unified Medical Language System (UMLS). Obtaining the terms list can occur automatically by natural language processing algorithms, being that the use of rules to identify information in texts allows the expert's knowledge to be coupled to the algorithm, and it can be performed by techniques based on Machine Learning. When it comes to mapping terms using the 7-Axis model of the International Classification for Nursing Practice (ICNP®), the process can also be automated through natural language processing algorithms such as POS-tagger and the syntactic parser. Conclusion: the cross-mapping method can be intensified by the use of natural language processing algorithms. However, even in cases of automatic mapping, the validation of the results by specialists should not be discarded.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-07072019000100601
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-07072019000100601
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1980-265x-tce-2017-0187
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de Santa Catarina, Programa de Pós Graduação em Enfermagem
publisher.none.fl_str_mv Universidade Federal de Santa Catarina, Programa de Pós Graduação em Enfermagem
dc.source.none.fl_str_mv Texto & Contexto - Enfermagem v.28 2019
reponame:Texto & contexto enfermagem (Online)
instname:Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
instname_str Universidade Federal de Santa Catarina (UFSC)
instacron_str UFSC
institution UFSC
reponame_str Texto & contexto enfermagem (Online)
collection Texto & contexto enfermagem (Online)
repository.name.fl_str_mv Texto & contexto enfermagem (Online) - Universidade Federal de Santa Catarina (UFSC)
repository.mail.fl_str_mv textoecontexto@nfr.ufsc.br
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