A rapid review on the application of common data models in healthcare: Recommendations for data governance and federated learning in artificial intelligence development
Development and implementation of CDMs is a collaborative and iterative process, highly affected by the boundaries set by the individual federated learning partners, and the nature of their data. Interdisciplinary collaboration in application of CDMs for federated learning and data governance of health data is mandatory, with a call to increase domain expert involvement in data management.
Authors
- Ville Kytö (ORCID: https://orcid.org/0000-0002-4521-1093)
- Hanna von Gerich
- Peter Lundberg (ORCID: https://orcid.org/0000-0001-8661-2232)
- Taridzo Chomutare (ORCID: https://orcid.org/0000-0003-3603-175X)
- Troels Siggaard (ORCID: https://orcid.org/0000-0003-0235-6150)
- Laura‐Maria Peltonen (ORCID: https://orcid.org/0000-0001-5740-6480)
Institutions
- Linköping University (SE)
- University of Copenhagen (DK)
- University of Turku (FI)
- Turku University of Applied Sciences (FI)
- University of Eastern Finland (FI)
- Turku University Hospital (FI)
- NORCE Research AS (NO)
- Finland University (FI)
- Region of Southern Denmark (DK)
- Linköping University Hospital (SE)
- Region Östergötland
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251395536
- Citations
- 1
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- Stockholms Universitet
- Socialstyrelsen