{
  "id": 8919,
  "url": "https://doi.org/10.1038/s42256-021-00337-8",
  "title": "End-to-end privacy preserving deep learning on multi-institutional medical imaging",
  "summary": "",
  "authors": "Georgios Kaissis, Alexander Ziller, Jonathan Passerat‐Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask",
  "category": "research",
  "topics": "privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2021-05-24T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:47.095Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8919",
  "original_url": "https://doi.org/10.1038/s42256-021-00337-8",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}