Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Letras de Hoje (Online) |
Texto Completo: | https://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/30955 |
Resumo: | In recent years, Mild Cognitive Impairment (MCI) has received a great deal of attention, as it may represent a pre-clinical state of Alzheimer´s disease (AD). In the distinction between healthy elderly (CTL) and MCI patients, automated discourse analysis tools have been applied to narrative transcripts in English and in Brazilian Portuguese. However, the absence of sentence boundary segmentation in transcripts prevents the direct application of methods that rely on these marks for the correct use of tools, such as taggers and parsers. To our knowledge, there are only a few studies evaluating automatic sentence segmentation in transcripts of neuropsychological tests. The purpose of this study is to investigate the impact ofthe automatic sentence segmentation method DeepBond on nine syntactic complexity metrics extracted of transcripts of CTL and MCI patients. |
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Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated systemDetecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated systemClinical diagnosisMild cognitive impairmentAutomatic sentence segmentationSyntactic complexity metricsAutomated discourse analysis toolsDiagnóstico clínicoComprometimento cognitivo leveSegmentação automática de sentençaMétricas de complexidade sintáticaFerramentas de análise do discursoIn recent years, Mild Cognitive Impairment (MCI) has received a great deal of attention, as it may represent a pre-clinical state of Alzheimer´s disease (AD). In the distinction between healthy elderly (CTL) and MCI patients, automated discourse analysis tools have been applied to narrative transcripts in English and in Brazilian Portuguese. However, the absence of sentence boundary segmentation in transcripts prevents the direct application of methods that rely on these marks for the correct use of tools, such as taggers and parsers. To our knowledge, there are only a few studies evaluating automatic sentence segmentation in transcripts of neuropsychological tests. The purpose of this study is to investigate the impact ofthe automatic sentence segmentation method DeepBond on nine syntactic complexity metrics extracted of transcripts of CTL and MCI patients.In recent years, Mild Cognitive Impairment (MCI) has received a great deal of attention, as it may represent a pre-clinical state of Alzheimer´s disease (AD). In the distinction between healthy elderly (CTL) and MCI patients, automated discourse analysis tools have been applied to narrative transcripts in English and in Brazilian Portuguese. However, the absence of sentence boundary segmentation in transcripts prevents the direct application of methods that rely on these marks for the correct use of tools, such as taggers and parsers. To our knowledge, there are only a few studies evaluating automatic sentence segmentation in transcripts of neuropsychological tests. The purpose of this study is to investigate the impact ofthe automatic sentence segmentation method DeepBond on nine syntactic complexity metrics extracted of transcripts of CTL and MCI patients.***Detecção de comprometimento cognitivo leve em narrativas em Português Brasileiro: primeiros passos para um sistema automatizado***Nos últimos anos, o Comprometimento Cognitivo Leve (CCL) tem recebido bastante atenção, uma vez que pode representar um estado pré-clínico da Doença de Alzheimer (DA). Na distinção entre idosos saudáveis (CTL) e pacientes com CCL, ferramentas de análise automática do discurso têm sido aplicadas a transcrições de narrativas em inglês e em português brasileiro. No entanto, a ausência da segmentação dos limites da sentença em transcrições impede a aplicação direta de métodos que empregam essas pontuações para o uso correto de ferramentas, como taggers e parsers. Segundo nosso conhecimento, há poucos estudos avaliando a segmentação automática de sentenças em transcrições de testes neuropsicológicos. O propósito deste estudo é investigar o impacto do método DeepBond para segmentação automática de sentenças em nove métricas de complexidade sintática extraídas de transcrições de CTL e de pacientes com CCL.Editora da PUCRS - ediPUCRS2018-06-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/3095510.15448/1984-7726.2018.1.30955Letras de Hoje; Vol. 53 No. 1 (2018): Language in a Psycho/Neurolinguistic and Cognitive Neuroscience perspective; 48-58Letras de Hoje; Vol. 53 Núm. 1 (2018): Linguagem na perspectiva da Psico/Neurolinguística e da Neurociência Cognitiva; 48-58Letras de Hoje; v. 53 n. 1 (2018): Linguagem na perspectiva da Psico/Neurolinguística e da Neurociência Cognitiva; 48-581984-77260101-333510.15448/1984-7726.2018.1reponame:Letras de Hoje (Online)instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)instacron:PUC_RSenghttps://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/30955/16915Copyright (c) 2018 Letras de Hojeinfo:eu-repo/semantics/openAccessTreviso, Marcos Viníciusdos Santos, Leandro BorgesShulby, ChristopherHübner, Lilian CristineMansur, Letícia LessaAluísio, Sandra Maria2018-06-27T15:36:22Zoai:ojs.revistaseletronicas.pucrs.br:article/30955Revistahttps://revistaseletronicas.pucrs.br/ojs/index.php/falePRIhttps://revistaseletronicas.pucrs.br/ojs/index.php/fale/oaieditora.periodicos@pucrs.br || letrasdehoje@pucrs.br1984-77260101-3335opendoar:2018-06-27T15:36:22Letras de Hoje (Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)false |
dc.title.none.fl_str_mv |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
title |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
spellingShingle |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system Treviso, Marcos Vinícius Clinical diagnosis Mild cognitive impairment Automatic sentence segmentation Syntactic complexity metrics Automated discourse analysis tools Diagnóstico clínico Comprometimento cognitivo leve Segmentação automática de sentença Métricas de complexidade sintática Ferramentas de análise do discurso |
title_short |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
title_full |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
title_fullStr |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
title_full_unstemmed |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
title_sort |
Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system |
author |
Treviso, Marcos Vinícius |
author_facet |
Treviso, Marcos Vinícius dos Santos, Leandro Borges Shulby, Christopher Hübner, Lilian Cristine Mansur, Letícia Lessa Aluísio, Sandra Maria |
author_role |
author |
author2 |
dos Santos, Leandro Borges Shulby, Christopher Hübner, Lilian Cristine Mansur, Letícia Lessa Aluísio, Sandra Maria |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Treviso, Marcos Vinícius dos Santos, Leandro Borges Shulby, Christopher Hübner, Lilian Cristine Mansur, Letícia Lessa Aluísio, Sandra Maria |
dc.subject.por.fl_str_mv |
Clinical diagnosis Mild cognitive impairment Automatic sentence segmentation Syntactic complexity metrics Automated discourse analysis tools Diagnóstico clínico Comprometimento cognitivo leve Segmentação automática de sentença Métricas de complexidade sintática Ferramentas de análise do discurso |
topic |
Clinical diagnosis Mild cognitive impairment Automatic sentence segmentation Syntactic complexity metrics Automated discourse analysis tools Diagnóstico clínico Comprometimento cognitivo leve Segmentação automática de sentença Métricas de complexidade sintática Ferramentas de análise do discurso |
description |
In recent years, Mild Cognitive Impairment (MCI) has received a great deal of attention, as it may represent a pre-clinical state of Alzheimer´s disease (AD). In the distinction between healthy elderly (CTL) and MCI patients, automated discourse analysis tools have been applied to narrative transcripts in English and in Brazilian Portuguese. However, the absence of sentence boundary segmentation in transcripts prevents the direct application of methods that rely on these marks for the correct use of tools, such as taggers and parsers. To our knowledge, there are only a few studies evaluating automatic sentence segmentation in transcripts of neuropsychological tests. The purpose of this study is to investigate the impact ofthe automatic sentence segmentation method DeepBond on nine syntactic complexity metrics extracted of transcripts of CTL and MCI patients. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-06-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/30955 10.15448/1984-7726.2018.1.30955 |
url |
https://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/30955 |
identifier_str_mv |
10.15448/1984-7726.2018.1.30955 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistaseletronicas.pucrs.br/ojs/index.php/fale/article/view/30955/16915 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Letras de Hoje info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Letras de Hoje |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora da PUCRS - ediPUCRS |
publisher.none.fl_str_mv |
Editora da PUCRS - ediPUCRS |
dc.source.none.fl_str_mv |
Letras de Hoje; Vol. 53 No. 1 (2018): Language in a Psycho/Neurolinguistic and Cognitive Neuroscience perspective; 48-58 Letras de Hoje; Vol. 53 Núm. 1 (2018): Linguagem na perspectiva da Psico/Neurolinguística e da Neurociência Cognitiva; 48-58 Letras de Hoje; v. 53 n. 1 (2018): Linguagem na perspectiva da Psico/Neurolinguística e da Neurociência Cognitiva; 48-58 1984-7726 0101-3335 10.15448/1984-7726.2018.1 reponame:Letras de Hoje (Online) instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) instacron:PUC_RS |
instname_str |
Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) |
instacron_str |
PUC_RS |
institution |
PUC_RS |
reponame_str |
Letras de Hoje (Online) |
collection |
Letras de Hoje (Online) |
repository.name.fl_str_mv |
Letras de Hoje (Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) |
repository.mail.fl_str_mv |
editora.periodicos@pucrs.br || letrasdehoje@pucrs.br |
_version_ |
1799128782015037440 |