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...

Celý popis

Podrobná bibliografia

Vydané v:	JMIR diabetes Ročník 10; s. e72874
Hlavní autori:	Sarani Rad, Fatemeh, Li, Juan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Canada JMIR Publications 04.07.2025
Predmet:	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 prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!