ArticleAlzheimer's & dementia (Amsterdam, Netherlands)
Relationship between language features extracted through NLP and clinically diagnosed Alzheimer's disease and mild cognitive impairment in Slovak.
Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Relationship between language features extracted through NLP and clinically diagnosed Alzheimer's disease and mild cognitive impairment in Slovak.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Detecting CSF-validated Alzheimer's disease from spontaneous speech in German: an interpretable end-to-end machine-learning framework.Frontiers in neurologyArticle
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Abstract
backgroundDementia, particularly Alzheimer's disease (AD), affects language, especially lexical-semantic processing. Discourse analysis using NLP methods can aid early detection, but research in inflectional languages like Slovak is limited.
methodsSpeech samples from 216 Slovak-speaking participants (64 AD, 44 MCI, 108 HC) were collected using a picture description task and analyzed for lexical complexity using 15 NLP-based measures.
resultsSeveral lexical complexity measures, including GTTR, UBER, SICHEL, MTLD, HDD and others, significantly differentiated AD or MCI from healthy controls. Some measures (UBER, YULEI, HONORE) also distinguished between AD and MCI.
conclusionLexical complexity metrics can serve as non-invasive linguistic indicators of neurodegenerative diseases, demonstrating diagnostic relevance for early detection of AD and MCI in Slovak. Highlights: Lexical complexity metrics effectively differentiate between healthy controls, MCI, and AD in Slovak speakers.Measures such as GTTR, UBER, and HONOR exhibit strong diagnostic potential for neurodegenerative diseases.Education significantly influences linguistic deficits, with higher education correlating to reduced cognitive decline.Findings underscore the importance of studying minority languages for advancing AD and MCI diagnostics.
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