{
  "id": 171,
  "url": "https://arxiv.org/abs/2607.05880v1",
  "title": "Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context",
  "summary": "Imaging demand is growing faster than the radiology workforce can expand, and reporting backlogs cannot be resolved through training and recruitment alone. The most direct opportunity is reducing the time and effort radiologists spend producing reports, a task that requires interpreting images, integrating clinical history and prior studies, and drafting structured findings. We present Harrison.Rad 1.5 (HR1.5), a radiology-specific multimodal large language model that accepts interleaved text an",
  "authors": "Suneeta Mall, Vladimir Nekrasov, Ashnil Kumar, Sajith Karunasena, Aiden Nibali, Alix Bird et al.",
  "category": "research",
  "topics": "jobs-economy,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-07T06:23:08.000Z",
  "fetched_at": "2026-07-14T14:14:19.970Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/171",
  "original_url": "https://arxiv.org/abs/2607.05880v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}