Semantic mapping in Alzheimer's disease: Measuring semantic distance using Natural Language Processing

Semantic distance, as measured using NLP techniques, has the potential to distinguish individuals with Alzheimer's disease from those without. A shorter semantic distance, which was observed in the AD group, may reflect an inefficient and disrupted semantic network. An impaired semantic system may restrict access to semantic representations that are more distant from the core concept. Enhancing understanding of semantic systems in AD may lead to a more nuanced linguistic profile that can be used to monitor disease progress. This study contributes to the growing evidence for the role of computational tools in analyzing language-based assessments to advance understanding of semantic deficits in dementia. References 1. DementiaBank. https://dementia.talkbank.org/ 2. Reilly, J., et al. (2024). https://doi.org/10.3758/s13423-024-02556-7.