Enhanced Diabetes Detection via a Privacy-Preserving Federated Learning Framework
Background: The integration of artificial intelligence (AI) in healthcare depends on striking a balance between patient privacy and clinical utility. The standard methods often compromise one for the other, preventing the development of trustworthy healthcare AI.Objective: This paper aims to resolve...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Prague University of Economics and Business
2026-06-01
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| coleção: | Acta Informatica Pragensia |
| Assuntos: | |
| Acesso em linha: | https://aip.vse.cz/artkey/aip-202602-0002_enhanced-diabetes-detection-via-a-privacy-preserving-federated-learning-framework.php |
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