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

      Myhre, Jonas Nordhaug; Tejedor Hernandez, Miguel Angel; Launonen, Ilkka Kalervo; El Fathi, Anas; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-11)
      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 control algorithms. The motivation for using policy gradient algorithms comes from the fact that adaptively ...