In-Silico Evaluation of Glucose Regulation Using Policy Gradient Reinforcement Learning for Patients with Type 1 Diabetes Mellitus

In-Silico Evaluation of Glucose Regulation Using Policy Gradient Reinforcement Learning for Patients with Type 1 Diabetes Mellitus

In this paper, we test and evaluate policy gradient reinforcement learning for automated blood glucose control in patients with Type 1 Diabetes Mellitus. Recent research has shown that reinforcement learning is a promising approach to accommodate the need for individualized blood glucose level contr...

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Bibliographic Details
Main Authors: Jonas Nordhaug Myhre, Miguel Tejedor, Ilkka Kalervo Launonen, Anas El Fathi, Fred Godtliebsen
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Applied Sciences
Subjects:
reinforcement learning
Type 1 Diabetes Mellitus
policy gradient
deep learning
artificial pancreas
Online Access:https://www.mdpi.com/2076-3417/10/18/6350

Internet

https://www.mdpi.com/2076-3417/10/18/6350

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