Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals
Overall, the approach proved to be feasible in implementation and competitive in accuracy, specifically when the model was fine-tuned to the subject's data.
Authors
- Stephan Jonas (ORCID: https://orcid.org/0000-0002-3687-6165)
- Maximilian Kapsecker (ORCID: https://orcid.org/0000-0002-3907-0749)
Institutions
- University Hospital Bonn (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1371/journal.pdig.0000793
- Citations
- 4
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 5.55