{
  "id": 4414,
  "url": "https://arxiv.org/abs/2605.13046v1",
  "title": "An Agentic LLM-Based Framework for Population-Scale Mental Health Screening",
  "summary": "Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from electronic records, telemedicine platforms, and population-level screening programs. At the same time, the emergence of novel AI-based approaches in healthcare calls for intelligent frameworks capable of processing domain-specific unstructured clinical information while adapting to patient-specific needs. This paper proposes an agentic framework for",
  "authors": "Giuliano Lorenzoni, Paulo Alencar, Donald Cowan",
  "category": "research",
  "topics": "healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-13T06:08:43.000Z",
  "fetched_at": "2026-07-14T16:30:59.236Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4414",
  "original_url": "https://arxiv.org/abs/2605.13046v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}