{
  "id": 17920,
  "url": "https://arxiv.org/abs/2608.07378v1",
  "title": "LSEAD: A Privacy-Preserving LLM-Based Speech Analysis Framework for Early Alzheimer's Disease Screening",
  "summary": "Early diagnosis of Alzheimer's disease (AD) is critical for enabling timely interventions that may slow disease progression and improve patient outcomes. There is a growing need for AD detection methods that are non-invasive and cost-effective, especially in real-world clinical settings with diverse patient populations and recording conditions. Speech-based screening addresses these needs by using natural speech collected without specialized equipment. Recent advances in large language models (L",
  "authors": "Xin Wang, Yingchao Huang, Yuhan Su, Shanshan Yao, Wei Peng",
  "category": "research",
  "topics": "privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-07T16:21:00.000Z",
  "fetched_at": "2026-08-10T05:10:00.488Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17920",
  "original_url": "https://arxiv.org/abs/2608.07378v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}