Detecting ADHD through natural language processing and stylometric analysis of adolescent narratives
These findings suggest that NLP and stylometry can enhance ADHD diagnostics by providing objective linguistic markers, thereby improving both its understanding and diagnostic procedures. Further research is needed to validate these methods in larger and more diverse populations.
Authors
- Elena Poznyak (ORCID: https://orcid.org/0000-0001-8079-9753)
- Florian Cafiero (ORCID: https://orcid.org/0000-0002-1951-6942)
- Jessica Lee Samson (ORCID: https://orcid.org/0000-0002-7396-3161)
- Martin Debbané (ORCID: https://orcid.org/0000-0002-4677-8753)
- Simon Gabay (ORCID: https://orcid.org/0000-0001-9094-4475)
- Halima Rafi (ORCID: https://orcid.org/0000-0003-0102-8294)
- Juan Barrios
Institutions
- University of Geneva (CH)
- École Nationale des Chartes (FR)
- University College London (GB)
Publication Details
- Journal
- Frontiers in Child and Adolescent Psychiatry
- Published
- 2025-05-09
- DOI
- https://doi.org/10.3389/frcha.2025.1519753
- Citations
- 3
- Primary Topic
- Attention Deficit Hyperactivity Disorder
- Type
- article
- Field-Weighted Citation Impact
- 4.41
Funders
- National Science Foundation
- Agenția Națională pentru Cercetare și Dezvoltare
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Agencia Nacional de Investigación y Desarrollo
- CHIST-ERA