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
m.fl.:
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
m.fl.:
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. oktober 2023
ARKIV /
DOI
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
Taridzo Fred Chomutare,
Miguel Angel Tejedor Hernandez,
Therese Olsen Svenning,
Luis Marco Ruiz,
Maryam Tayefi Nasrabadi,
Karianne Fredenfeldt Lind
m.fl.:
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
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
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. september 2020
ARKIV /
DOI
Alexandra Makhlysheva,
Luis Marco Ruiz,
Therese Olsen Svenning,
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Anne Torill Nordsletta
m.fl.:
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
m.fl.:
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 Trust Region Policy Optimization Reinforcement Learning for T1DM Closed-Loop Control
2019
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
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
m.fl.:
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