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Automated speech analysis to identify clinical, anatomical, and pathological variants of primary progressive aphasia

08.03.26 | JAMA Network
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About the Study : Can automated analysis of 1 to 2 minutes of connected speech yield interpretable profiles that distinguish primary progressive aphasia (PPA) variants and reflect neuroanatomical and neuropathologic substrates? In this cross-sectional study of 214 participants, Lasso multinomial modeling generated variant-specific speech profile scores that differentiated nonfluent PPA, logopenic PPA, and semantic PPA with high overall performance and showed expected atrophy associations. In an autopsy-confirmed subset, speech profiles also discriminated common neuropathologic classes. Results suggest that brief automated speech profiling may enable scalable, interpretable support for PPA differential diagnosis and monitoring.

Corresponding Author : Jet M. J. Vonk, PhD, PhD, Edward and Pearl Fein Memory and Aging Center, Department of Neurology, University of California San Francisco (UCSF), 675 Nelson Rising Ln, Ste 190, San Francisco, CA 94158 ( jet.vonk@ucsf.edu ).

10.1001/jamaneurol.2026.2520

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JAMA Neurology

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How to Cite This Article

APA:
JAMA Network. (2026, August 3). Automated speech analysis to identify clinical, anatomical, and pathological variants of primary progressive aphasia. Brightsurf News. https://www.brightsurf.com/news/LPEZY408/automated-speech-analysis-to-identify-clinical-anatomical-and-pathological-variants-of-primary-progressive-aphasia.html
MLA:
"Automated speech analysis to identify clinical, anatomical, and pathological variants of primary progressive aphasia." Brightsurf News, Aug. 3 2026, https://www.brightsurf.com/news/LPEZY408/automated-speech-analysis-to-identify-clinical-anatomical-and-pathological-variants-of-primary-progressive-aphasia.html.