Silva, S;
Altmann, A;
Gutman, B;
Lorenzi, M;
(2020)
Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare.
In:
MICCAI Workshop on Domain Adaptation and Representation Transfer MICCAI Workshop on Distributed and Collaborative Learning DART 2020, DCL 2020: Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning.
(pp. pp. 201-210).
Springer, Cham
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Abstract
While data in healthcare is produced in quantities never imagined before, the feasibility of clinical studies is often hindered by the problem of data access and transfer, especially regarding privacy concerns. Federated learning allows privacy-preserving data analyses using decentralized optimization approaches keeping data securely decentralized. There are currently initiatives providing federated learning frameworks, which are however tailored to specific hardware and modeling approaches, and do not provide natively a deployable production-ready environment. To tackle this issue, herein we propose an open-source federated learning frontend framework with application in healthcare. Our framework is based on a general architecture accommodating for different models and optimization methods. We present software components for clients and central node, and we illustrate the workflow for deploying learning models. We finally provide a real-world application to the federated analysis of multi-centric brain imaging data.
| Type: | Proceedings paper |
|---|---|
| Title: | Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare |
| Event: | MICCAI Workshop on Distributed And Collaborative Learning |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-60548-3_20 |
| Publisher version: | https://doi.org/10.1007/978-3-030-60548-3_20 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10113930 |
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