Natural language processing‐based classification of early Alzheimer's disease from connected speech
This study compared five types of connected speech for the detection of early Alzheimer's disease (AD). Autobiographical interviews yielded a higher specificity than scene descriptions. A preceding clinical AD classification task can refine the performance of amyloid status classification in cognitively healthy individuals.
Authors
- Patrick Dupont (ORCID: https://orcid.org/0000-0003-1980-2540)
- Bastiaan Tamm (ORCID: https://orcid.org/0000-0001-6094-4060)
- Ella Eycken
- Helena Balabin (ORCID: https://orcid.org/0000-0002-6392-9306)
- Rik R. Vandenberghe (ORCID: https://orcid.org/0000-0001-6237-2502)
- Marie‐Francine Moens (ORCID: https://orcid.org/0000-0002-3732-9323)
- Hugo Van hamme (ORCID: https://orcid.org/0000-0003-1331-5186)
- Steffi De Meyer
- Laure Spruyt (ORCID: https://orcid.org/0000-0002-0618-5005)
- Ines Kabouche
- Nathalie Dusart
- Kevin Statz (ORCID: https://orcid.org/0009-0009-7400-7006)
Institutions
- Allen Institute for Brain Science (US)
- VIB-KU Leuven Center for Brain & Disease Research (BE)
- KU Leuven (BE)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1002/alz.14530
- Citations
- 3
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 4.41
Funders
- Fonds Wetenschappelijk Onderzoek
- KU Leuven
- Vlaamse regering