Miguel Angel Tejedor Hernandez

Bio

Miguel Ángel Tejedor Hernández is a researcher in health analytics at the Norwegian Centre for E-health Research, and a PhD Candidate at the University of Tromsø – The Artic University of Norway (UiT). He hold a Master degree in Telecommunications Engineering, and a second Master in Telecommunication Technologies, both from the University of Las Palmas de Gran Canaria (ULPGC).

His research interests focus on applied machine learning for healthcare. Concretely, his recent research has been focused on developing algorithms for blood glucose control in type 1 diabetes patients using machine learning techniques. Previously, his research was focused on developing algorithms to detect brain cancer using hyperspectral imaging and machine learning techniques.

Miguel Angel Tejedor Hernandez

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Telefon: 926 99 162

Stilling: Forsker

Avdeling: Helsedata og analyse

CRIStin-profil

Miguel Angels publikasjoner i Cristin

Tittel År Kategori
In-silico evaluation of glucose regulation using policy gradient reinforcement learning for patients with type 1 diabetes mellitus 2020 Academic article
Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities 2020 Academic article
Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function 2020 Popular scientific lecture
Including T1D knowledge in deep reinforcement learning reduces hypoglycemia 2020 Poster
Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function 2020 Poster
Reinforcement learning application in diabetes blood glucose control: A systematic review 2020 Academic literature review
In-silico Evaluation of Trust Region Policy Optimization Reinforcement Learning for T1DM Closed-Loop Control 2019 Poster
In-silico Evaluation of Type-1 Diabetes Closed-Loop Control using Deep Reinforcement Learning 2019 Poster
A Decision Support Tool for Optimal Control of Planet Temperature Using Reinforcement Learning 2018 Lecture
A Novel Use of Hyperspectral Images for Human Brain Cancer Detection using In-Vivo Samples 2016 Popular scientific lecture
Brain tumours detection by semi-supervised algorithm combining spectral unmixing and supervised classification using hyperspectral imaging 2016 Masters thesis
Identification of brain tumours by studying the shape and composition of brain tissues using hyperspectral imaging 2015 Masters thesis