Detecting mild cognitive impairment in narratives in Brazilian Portuguese: first steps towards a fully automated system

Marcos Vinícius Treviso, Leandro Borges dos Santos, Christopher Shulby, Lilian Cristine Hübner, Letícia Lessa Mansur, Sandra Maria Aluísio

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 of
the 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.


Palavras-chave


Diagnóstico clínico; Comprometimento cognitivo leve; Segmentação automática de sentença; Métricas de complexidade sintática; Ferramentas de análise do discurso

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DOI: http://dx.doi.org/10.15448/1984-7726.2018.1.30955

e-ISSN: 1984-7726

ISSN-L: 0101-3335

 

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Apoio Institucional – fev./dez. 2012 referente ao Edital MCTI/CNPq/MEC/CAPES Nº. 15/2011.



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