{
  "id": 12733,
  "url": "https://link.springer.com/article/10.1007/s10462-026-11649-9",
  "title": "Large language models and multimodal AI for mental health: a systematic review of early diagnosis and monitoring",
  "summary": "Mental health disorders (e.g., depression, anxiety, post-traumatic stress disorder (PTSD), bipolar disorder) represent a pressing global challenge, and early diagnosis with continuous monitoring is critical for effective intervention. However, traditional diagnostic methods, relying on patient self-reports and clinical interviews, are subjective and often miss subtle early warning signs, a problem compounded by stigma and limited access to care. In response, recent advances in artificial intelli",
  "authors": null,
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-22T00:00:00.000Z",
  "fetched_at": "2026-07-23T05:10:49.458Z",
  "source_slug": "x-artificial-intelligence-review",
  "source_name": "Artificial Intelligence Review",
  "source_homepage": "https://link.springer.com/journal/10462",
  "ethics_ai_record_url": "https://ethics.ai/record/12733",
  "original_url": "https://link.springer.com/article/10.1007/s10462-026-11649-9",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}