Toward a Speech-Based Model of Premanifest Huntington’s Disease Progression Using Deep Neural Networks
A brief, structured speech task combined with deep learning enabled accurate classification of preHD. These findings support speech analysis as a scalable, objective tool for early disease detection and monitoring.
Authors
- S Frank
- Nate Blaylock
- Raymond Brueckner
- Japleen Kaur (ORCID: https://orcid.org/0009-0006-6553-0944)
- Vinod Subramanian
- Simon Laganiere
- Jody Corey-bloom
- Henry O'Connell
- Luis A. Sierra
- Namhee Kwon
Institutions
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- University of California San Diego (US)
- Provo College (US)
Publication Details
- Journal
- Digital Biomarkers
- Published
- 2026-01-19
- DOI
- https://doi.org/10.1159/000549327
- Primary Topic
- Genetic Neurodegenerative Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00