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Using Generative Artificial Intelligence to Classify Primary Progressive Aphasia from Connected Speech.

Neguine Rezaii1,2, Megan Quimby1, Bonnie Wong1,3

  • 1Frontotemporal Disorders Unit, Massachusetts General Hospital & Harvard Medical School, Boston MA, USA.

Medrxiv : the Preprint Server for Health Sciences
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Summary
This summary is machine-generated.

Artificial intelligence and natural language processing accurately classified subtypes of Primary Progressive Aphasia (PPA) using speech analysis. This approach enhances early dementia diagnosis and understanding of neurodegenerative language disorders.

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Area of Science:

  • Neuroscience
  • Computational Linguistics
  • Medical Diagnostics

Background:

  • Primary Progressive Aphasia (PPA) diagnosis relies on cognitive profiles, with ongoing debate on its variants and classification.
  • Identifying distinctive linguistic markers for PPA variant classification remains a challenge.

Conclusions:

  • AI and NLP offer powerful tools for refining early-stage dementia diagnosis, specifically for PPA.
  • The study deepens understanding of PPA phenotypes, neurobiology of language, and diagnostic accuracy.
  • Speech analysis, particularly verb frequency, provides valuable insights for classifying PPA variants.