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...
I tiakina i:
| Ngā kaituhi matua: | , , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Prague University of Economics and Business
2026-06-01
|
| Rangatū: | Acta Informatica Pragensia |
| Ngā marau: | |
| Urunga tuihono: | https://aip.vse.cz/artkey/aip-202602-0002_enhanced-diabetes-detection-via-a-privacy-preserving-federated-learning-framework.php |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|