From Federated Learning to Publicly Facing Platform; Proof-of-Concept of the STRONG AYA Information Portal
Information on health data is often shrouded in exclusivity and sharing of such information is normally difficult and time-locked for numerous reasons. Federated learning (FL) regularly accelerates knowledge sharing, yet it is not fully exploited to alleviate overall data exclusivity and time constraints. Here, we present a proof-of-concept for a public FL-based info portal of the STRONG AYA Initiative.
Authors
- Leonard Wee (ORCID: https://orcid.org/0000-0003-1612-9055)
- Joshi Hogenboom (ORCID: https://orcid.org/0000-0003-1278-3295)
- André Dekker (ORCID: https://orcid.org/0000-0002-0422-7996)
- Olga Husson (ORCID: https://orcid.org/0000-0002-1387-8686)
- Aiara Lobo Gomes (ORCID: https://orcid.org/0000-0003-4670-6036)
- Winette van der Graaf
Institutions
- Maastricht University Medical Centre (NL)
- The Netherlands Cancer Institute (NL)
- Erasmus MC Cancer Institute (NL)
- Maastro Clinic (NL)
- Erasmus University Rotterdam (NL)
Publication Details
- Journal
- Studies in health technology and informatics
- Published
- 2025-05-15
- DOI
- https://doi.org/10.3233/shti250407
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.00