Miguel Angel Tejedor Hernandez
Taridzo Chomutare,
Therese Olsen Svenning,
Miguel Angel Tejedor Hernandez,
Phuong Dinh Ngo,
Andrius Budrionis,
Kaisa Markljung
m.fl.:
Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial
Phuong Dinh Ngo,
Miguel Angel Tejedor Hernandez,
Taridzo Fred Chomutare,
Andrius Budrionis,
Therese Olsen Svenning,
Torbjørn Torsvik
m.fl.:
Domain-Specific Pretraining and Evaluation of NorDeClin-BERT for ICD-10 Code Prediction in Norwegian Clinical Texts
Journal of Medical Internet Research AI (JMIR AI) 2025 DOI
Iver Martinsen,
Steffen Aagaard Sørensen,
Samuel Ortega,
Fred Godtliebsen,
Miguel Angel Tejedor Hernandez,
Eirik Myrvoll-Nilsen
:
Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts
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
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
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
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
Miguel Angel Tejedor Hernandez,
Ashenafi Zebene Woldaregay,
Fred Godtliebsen
:
Reinforcement learning application in diabetes blood glucose control: A systematic review
Iver Martinsen,
Fred Godtliebsen,
Steffen Aagaard Sørensen,
Eirik Myrvoll-Nilsen,
Samuel Ortega Sarmiento,
Miguel Angel Tejedor Hernandez
:
Are humans an AI uncertain about the same things?
2024
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
Nasjonalt senter for e-helseforskning 2023 FULLTEKST
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
Nasjonalt senter for e-helseforskning 2022 FULLTEKST
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
:
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
Miguel Angel Tejedor Hernandez,
Jonas Nordhaug Myhre
:
Including T1D knowledge in deep reinforcement learning reduces hypoglycemia
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
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
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
:
Identification of brain tumours by studying the shape and composition of brain tissues using hyperspectral imaging
Universidad de las Palmas de Gran Canaria 2015
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