arXiv (All)
open access
LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection
Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both lexical-semantic organization and speech production, including atypical pauses and word elongations. However, existing methods have yet to fully in
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Identification of Early Markers of Alzheimer's Disease by Using Eye Tracking in Reading.#826341
- The Utility of Speech and Language Analytics for Screening Alzheimer's Disease.#315801
- Explainable and Generalisable LLM-based Cognitive Decline Detection with Spontaneous Speech#1119290
- Unmasking preclinical Alzheimer's pathology: auditory distraction cost and occupational reserve jointly discriminate amyloid positivity in subjective cognitive decline.#1068997
- Developments in understanding early onset Alzheimer's disease#1133139
Record · ID 998471
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive