# OnCo record federated-learning-medical-ai (technology). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)". Whole corpus: https://onco.cc/api/v1/onco.nt
@prefix schema: <https://schema.org/> .
@prefix onco: <https://onco.cc/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://onco.cc/technologies/federated-learning-medical-ai/>
  a schema:MedicalTherapy ;
  onco:kind "technology" ;
  schema:identifier "federated-learning-medical-ai" ;
  schema:name "Federated learning and privacy-preserving AI"@en ;
  schema:description "Federated learning trains one AI model across hospitals by exchanging model updates, not patient data, so a pathology or radiology model learns from every site while records stay behind each firewall. Owkin, NVIDIA FLARE and the MELLODDY pharma consortium use it; governance overhead and differing data across sites are the practical obstacles."@en ;
  schema:url <https://onco.cc/technologies/federated-learning-medical-ai/> ;
  schema:dateModified "2026-09-08"^^xsd:date ;
  schema:citation <https://doi.org/10.1038/s41746-020-00323-1> ;
  onco:status "emerging" ;
  onco:tag "supporting" ;
  onco:sections <https://onco.cc/fronts/ai-computation/> ;
  onco:technologies <https://onco.cc/technologies/pathology-foundation-model/>, <https://onco.cc/technologies/radiology-ai-screening/>, <https://onco.cc/technologies/ai-compute-platforms/>, <https://onco.cc/technologies/oncology-real-world-data/> ;
  onco:companies <https://onco.cc/companies/nvidia/>, <https://onco.cc/companies/owkin/> ;
  onco:keyPapers <https://onco.cc/key-papers/paper-rieke-npj-digit-med/> .