{
  "id": 592,
  "url": "https://arxiv.org/abs/2606.26494v2",
  "title": "Clinical Harness for Governable Medical AI Skill Ecosystems",
  "summary": "Medical AI remains organized around isolated models, whereas care requires accountable capabilities that persist across time. We define clinical AI skills and propose the Clinical Harness, a runtime governance architecture that registers, orchestrates, constrains and monitors them. Using osteoporosis as an exemplar, we show how knowledge-driven, data-driven and physics-enhanced skills can support lifecycle care and provide a governed substrate for future medical agents.",
  "authors": "Tianhan Xu, Lei Bao, Zhe Hu, Tian Shen, Yongxiang Wang",
  "category": "research",
  "topics": "regulation,healthcare,agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-25T00:53:24.000Z",
  "fetched_at": "2026-07-14T14:14:37.250Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/592",
  "original_url": "https://arxiv.org/abs/2606.26494v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}