Standardization and Interoperability: Federated Learning’s Impact on EHR Systems and Health Informatics
Federated learning represents a transformative advancement in health informatics, addressing the critical need for seamless data exchange in the fragmented US healthcare landscape. By improving patient outcomes and operational efficiencies, federated learning paves the way for leveraging big data analytics on a nationwide scale.
Authors
- Herat Joshi
- Shenson Joseph (ORCID: https://orcid.org/0009-0001-5191-5556)
Institutions
- Twitter (United States) (US)
- University of North Dakota (US)
- National Great Rivers Research and Education Center (US)
Publication Details
- Journal
- Advances in Health Information Science and Practice
- Published
- 2025-01-01
- DOI
- https://doi.org/10.63116/ubym3803
- Citations
- 2
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 4.96