Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework

Effective diabetes management requires precise glycemic control to prevent both hypoglycemia and hyperglycemia, yet existing machine learning (ML) and reinforcement learning (RL) approaches often fail to balance competing objectives. Traditional RL-based glucose regulation systems primarily focus on...

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Vydáno v:	JMIR diabetes Ročník 10; s. e72874
Hlavní autoři:	Sarani Rad, Fatemeh, Li, Juan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Canada JMIR Publications 04.07.2025
Témata:	Artificial intelligence Automation Decision making Privacy multiobjective optimization privacy-preserving artificial intelligence diabetes management federated reinforcement learning AI blood glucose control reward shaping federated learning reinforcement learning
ISSN:	2371-4379, 2371-4379
On-line přístup:	Získat plný text
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