Natural Language Processing differentiates between Italian individuals with Nonfluent/Agrammatic from Logopenic variants of PPA
We implemented natural language processing to perform a machine-learning classification based on connected speech samples of Italian-speaking subjects. This approach has been applied for the first time to Italian PPA and demonstrated that key linguistic markers can be identified and compared across the two variants.
Authors
- Christian Salvatore (ORCID: https://orcid.org/0000-0001-9312-4675)
- Alessandro Introna (ORCID: https://orcid.org/0000-0002-3141-6442)
- Simona Aresta (ORCID: https://orcid.org/0000-0002-9032-6578)
- Petronilla Battista (ORCID: https://orcid.org/0000-0002-3120-1214)
- Serena Tagliente (ORCID: https://orcid.org/0009-0005-9489-6032)
- Paola Santacesaria
- Stefania Tagliente
- Rosa Capozzo
- Cinzia Palmirotta
- Christian Lunetta (ORCID: https://orcid.org/0000-0002-4788-1875)
- Allegra Benzini
- Alberto Benussi
Institutions
- University of Trieste (IT)
- Istituto Universitario di Studi Superiori di Pavia (IT)
- Istituti Clinici Scientifici Maugeri (IT)
- Ospedale Generale Regionale Francesco Miulli (IT)
- Global Brain Health Institute (US)
- University of Bari Aldo Moro (IT)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70857_105208
- Primary Topic
- Neurobiology of Language and Bilingualism
- Type
- article
- Field-Weighted Citation Impact
- 0.00