B1 Vertaisarvioitu muu artikkeli (esim. pääkirjoitus, letter, comment) tieteellisessä lehdessä
Federated learning’s uncomfortable truth: why human networks matter more than neural networks
Tekijät: Peltonen, Laura-Maria; Chomutare, Taridzo
Kustantaja: Oxford University Press (OUP)
Julkaisuvuosi: 2026
Lehti: Journal of the American Medical Informatics Association
Artikkelin numero: ocag047
ISSN: 1067-5027
eISSN: 1527-974X
DOI: https://doi.org/10.1093/jamia/ocag047
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Osittain avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1093/jamia/ocag047
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/523080445
Rinnakkaistallenteen lisenssi: CC BY
Rinnakkaistallennetun julkaisun versio: Kustantajan versio
Objectives
To examine real-world barriers to implementing federated learning in healthcare and highlight the organizational, regulatory, and socio-technical factors often overlooked in technical research.
Materials and Methods
Insights were derived from a 3-year implementation of a Nordic–Baltic federated health data network involving 5 countries and 9 institutions, incorporating legal, organizational, and cross-disciplinary perspectives.
Results
Structural challenges included coordination burdens, divergent interpretations of privacy and risk, epistemological gaps between disciplines, and the absence of legal frameworks for multi-country distributed learning in Europe. These constraints limited progress despite the availability of robust technical solutions.
Discussion
Technical privacy measures alone cannot replace trust-building, governance development, and cross-disciplinary translation work. Federated learning is more accurately understood as a socio-technical collaboration model rather than a purely technical architecture.
Conclusion
Pre-implementation planning, tiered participation models, and strengthened governance are essential to support equitable, sustainable, and clinically impactful adoption of federated learning in healthcare.
Ladattava julkaisu This is an electronic reprint of the original article. |
Julkaisussa olevat rahoitustiedot:
This work draws on insights generated within the FederatedHealth project, funded by Nordic Innovation and the work was supported by the Research Council of Finland (grant no. 372505).