Phuong Dinh Ngo,
Miguel Angel Tejedor Hernandez,
Therese Olsen Svenning,
Taridzo Fred Chomutare,
Andrius Budrionis,
Hercules Dalianis
:
Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model
Proceedings of the Workshop on Computational Approaches to Language Data Pseudonymization (CALD-pseudo 2024) 2024
ARKIV
Luis Marco Ruiz,
Miguel Angel Tejedor Hernandez,
Phuong Dinh Ngo,
Alexandra Makhlysheva,
Therese Olsen Svenning,
Kari Dyb
et al.:
A multinational study on artificial intelligence adoption: Clinical implementers' perspectives
International Journal of Medical Informatics 2024
DOI
Marit Dagny Kristine Jenssen,
Elisa Salvi,
Egil Andreas Fors,
Ole Andreas Nilsen,
Phuong Dinh Ngo,
Miguel Angel Tejedor Hernandez
et al.:
Exploring Pain Reduction through Physical Activity: A Case Study of Seven Fibromyalgia Patients
Tejedor H Miguel Angel,
Sigurd Hjerde,
Jonas Nordhaug Myhre,
Fred Godtliebsen
:
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes
Diagnostics (Basel) 07. Oct 2023
ARKIV /
DOI
Taridzo Fred Chomutare,
Miguel Angel Tejedor Hernandez,
Therese Olsen Svenning,
Luis Marco Ruiz,
Maryam Tayefi Nasrabadi,
Karianne Fredenfeldt Lind
et al.:
Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators
International Journal of Environmental Research and Public Health (IJERPH) 2022
ARKIV /
DOI
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Anas El Fathi,
Fred Godtliebsen
:
In-silico evaluation of glucose regulation using policy gradient reinforcement learning for patients with type 1 diabetes mellitus
Applied Sciences 11. Sep 2020
ARKIV /
DOI
Miguel Angel Tejedor Hernandez,
Ashenafi Zebene Woldaregay,
Fred Godtliebsen
:
Reinforcement learning application in diabetes blood glucose control: A systematic review
Artificial Intelligence in Medicine 2020
ARKIV /
DOI
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Maryam Tayefi,
Taridzo Chomutare,
Fred Godtliebsen
:
Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities
Alexandra Makhlysheva,
Luis Marco Ruiz,
Therese Olsen Svenning,
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Anne Torill Nordsletta
et al.:
Implementering av kunstig intelligens i norsk helsetjeneste: veien til utbredt bruk
Alexandra Makhlysheva,
Luis Marco Ruiz,
Therese Olsen Svenning,
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Maryam Tayefi Nasrabadi
et al.:
Implementation of artificial intelligence in Norwegian healthcare: The road to broad adoption
Tejedor H Miguel Angel
:
Glucose Regulation for In-Silico Type 1 Diabetes Patients Using Reinforcement Learning
UiT Norges arktiske universitet 2021
Miguel Angel Tejedor Hernandez,
Jonas Nordhaug Myhre
:
Including T1D knowledge in deep reinforcement learning reduces hypoglycemia
2020
Miguel Angel Tejedor Hernandez,
Jonas Nordhaug Myhre
:
Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function
2020
Miguel Angel Tejedor Hernandez,
Jonas Nordhaug Myhre
:
Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function
2020
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Fred Godtliebsen
:
In-silico Evaluation of Type-1 Diabetes Closed-Loop Control using Deep Reinforcement Learning
2019
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Fred Godtliebsen
:
In-silico Evaluation of Trust Region Policy Optimization Reinforcement Learning for T1DM Closed-Loop Control
2019
Phuong D. Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
A Decision Support Tool for Optimal Control of Planet Temperature Using Reinforcement Learning
2018
Himar Fabelo,
Samuel Ortega,
R. Guerra,
Gustavo Callico,
A. Szolna,
J. F. Piñeiro
et al.:
A Novel Use of Hyperspectral Images for Human Brain Cancer Detection using In-Vivo Samples
2016
Miguel Angel Tejedor Hernandez
:
Brain tumours detection by semi-supervised algorithm combining spectral unmixing and supervised classification using hyperspectral imaging
Universidad de las Palmas de Gran Canaria 2016
Miguel Angel Tejedor Hernandez
:
Identification of brain tumours by studying the shape and composition of brain tissues using hyperspectral imaging
Universidad de las Palmas de Gran Canaria 2015