{
  "id": 9021,
  "url": "https://doi.org/10.1145/3412357",
  "title": "Federated Learning in a Medical Context: A Systematic Literature Review",
  "summary": "Data privacy is a very important issue. Especially in fields like medicine, it is paramount to abide by the existing privacy regulations to preserve patients’ anonymity. However, data is required for research and training machine learning models that could help gain insight into complex correlations or personalised treatments that may otherwise stay undiscovered. Those models generally scale with the amount of data available, but the current situation often prohibits building large databases acr",
  "authors": "Bjarne Pfitzner, Nico Steckhan, Bert Arnrich",
  "category": "research",
  "topics": "regulation,privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2021-06-02T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:47.101Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9021",
  "original_url": "https://doi.org/10.1145/3412357",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}