Cristin-person-ID: 814334
Person

Miguel Angel Tejedor Hernandez

  • Stilling:
    Gjest
    ved Fakultet for naturvitenskap og teknologi ved UiT Norges arktiske universitet

Resultater Resultater

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. 2020, Applied Sciences. UIT, UNN, MCGILLVitenskapelig artikkel

Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities.

Ngo, Phuong; Tejedor Hernandez, Miguel Angel; Tayefi, Maryam; Chomutare, Taridzo; Godtliebsen, Fred. 2020, Applied Sciences. UIT, UNNVitenskapelig artikkel

Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function.

Tejedor Hernandez, Miguel Angel; Myhre, Jonas Nordhaug. 2020, Northern Lights Deep Learning Workshop. UITPopulærvitenskapelig foredrag

Including T1D knowledge in deep reinforcement learning reduces hypoglycemia.

Tejedor Hernandez, Miguel Angel; Myhre, Jonas Nordhaug. 2020, International Conference on Advanced Technologies & Treatments for Diabetes. UITPoster

Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function.

Tejedor Hernandez, Miguel Angel; Myhre, Jonas Nordhaug. 2020, Northern Lights Deep Learning Workshop. UITPoster
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