Iver Martinsen,
David Wade,
Fred Godtliebsen,
Benjamin Ricaud
:
The 3-billion fossil question: How to automate classification of microfossils
Artificial Intelligence in Geosciences 2024
ARKIV /
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
Fred Godtliebsen,
Eirik Myrvoll-Nilsen,
Lasse Holmström
:
Comments on: Data integration via analysis of subspaces (DIVAS)
Test (Madrid) 2024
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
Jonathan E Berezowski,
Thomas Andre Haugland Johansen,
Jonas Nordhaug Myhre,
Fred Godtliebsen
:
Variable Depth Bayesian Neural Networks Using Reversible Jumps
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
Isak Paasche Edvardsen,
Anna Teterina,
Thomas Haugland Johansen,
Jonas Nordhaug Myhre,
Fred Godtliebsen,
Napat Limchaichana Bolstad
:
Automatic detection of the mental foramen for estimating mandibular cortical width in dental panoramic radiographs: the seventh survey of the Tromsø Study (Tromsø7) in 2015-2016
Journal of International Medical Research 22. Nov 2022
ARKIV /
DOI
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
Stig Uteng,
Eduardo Quevedo,
Gustavo M. Callico,
Irene Castaño,
Gregorio Carretero,
Pablo Almeida
et al.:
Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing
Marit Dagny Kristine Jenssen,
Per Atle Bakkevoll,
Phuong Ngo,
Andrius Budrionis,
Asbjørn Johansen Fagerlund,
Maryam Tayefi
et al.:
Machine Learning in Chronic Pain Research: A Scoping Review
Maryam Tayefi,
Phuong Ngo,
Taridzo Chomutare,
Hercules Dalianis,
Elisa Salvi,
Andrius Budrionis
et al.:
Challenges and opportunities beyond structured data in analysis of electronic health records
Wiley Interdisciplinary Reviews: Computational Statistics 14. Feb 2021
ARKIV /
DOI
Thomas Haugland Johansen,
Steffen Aagaard Sørensen,
Kajsa Møllersen,
Fred Godtliebsen
:
Instance Segmentation of Microscopic Foraminifera
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
Giovanni Sebastiani,
Stig Uteng,
Fred Godtliebsen,
Jan Polàk,
Jan Brož
:
Estimation of Blood Glucose Concentration During Endurance Sports
International Journal of Biology and Biomedical Engineering 2020
ARKIV /
DOI
Samuel Ortega,
Martin Halicek,
Himar Fabelo,
Rafael Camacho,
Maria de La Luz Plaza,
Fred Godtliebsen
et al.:
Hyperspectral imaging for the detection of glioblastoma tumor cells in H&E slides using convolution neural networks
Samuel Ortega,
Martin Halicek,
Himar Fabelo,
Raul Guerra,
Carlos Lopez,
Marylene Lejaune
et al.:
Hyperspectral imaging and deep learning for the detection of breast cancer cells in digitized histological images
Proceedings of SPIE, the International Society for Optical Engineering 2020
FULLTEKST /
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
Stig Uteng,
Thomas Haugland Johansen,
Jose Ignacio Zaballos,
Samuel Ortega,
Lasse Holmström,
Gustavo M. Callico
et al.:
Early Detection of Change by Applying Scale-Space Methodology to Hyperspectral Images
Taridzo Chomutare,
Kassaye Yitbarek Yigzaw,
Andrius Budrionis,
Alexandra Makhlysheva,
Fred Godtliebsen,
Hercules Dalianis
:
De-identifying Swedish EHR text using public resources in the general domain
Studies in Health Technology and Informatics 2020
ARKIV /
DOI
Kajsa Møllersen,
Jon Yngve Hardeberg,
Fred Godtliebsen
:
A probabilistic bag-to-class approach to multiple-instance learning
Sebastian Andres Acuña Maldonado,
Ida Sundvor Opstad,
Fred Godtliebsen,
Balpreet Singh Ahluwalia,
Krishna Agarwal
:
Soft thresholding schemes for multiple signal classification algorithm
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
Thomas Haugland Johansen,
Kajsa Møllersen,
Samuel Ortega,
Himar Fabelo,
Aday Garcia,
Gustavo Callico
et al.:
Recent advances in hyperspectral imaging for melanoma detection
Wiley Interdisciplinary Reviews: Computational Statistics 2019
ARKIV /
DOI
Kristian Hindberg,
Jan Hannig,
Fred Godtliebsen
:
A novel scale-space approach for multinormality testing and the k-sample problem in the high dimension low sample size scenario
Phuong Ngo,
Maryam Tayefi,
Anne Torill Nordsletta,
Fred Godtliebsen
:
Food recommendation using machine learning for physical activities in patients with type 1 diabetes
John S. Hammond,
Fred Godtliebsen,
Sonja Eriksson Steigen,
I. Neil Guha,
Judy Wyatt,
Arthur Revhaug
et al.:
The effects of terlipressin and direct portacaval shunting on liver hemodynamics following 80% hepatectomy in the pig
David Wade,
Fred Godtliebsen,
Benjamin Ricaud,
Iver Martinsen
:
A deep learning pipeline for automatic microfossil analysis and classification
2024
Iver Martinsen,
David Wade,
Benjamin Ricaud,
Fred Godtliebsen
:
A deep learning pipeline for automatic microfossil analysis and classification
2024
Steffen Aagaard Sørensen,
Eirik Myrvoll-Nilsen,
Iver Martinsen,
Fred Godtliebsen,
Stamatia Galata,
Juho Junttila
et al.:
Detection and identification of environmental faunal proxies in digital images and video footage from northern Norwegian fjords and coastal waters using deep learning object detection algorithms
2024
Eirik Myrvoll-Nilsen,
Steffen Aagaard-Sørensen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
et al.:
Automated classification of microscopic foraminifera
2023
Fred Godtliebsen
:
Sparse networks in deep learning
2023
Fred Godtliebsen
:
Trans-dimensional Bayesian Deep Learning
2023
Fred Godtliebsen
:
Sparse Networks in Deep Learning
2023
Eirik Myrvoll-Nilsen,
Steffen Aagaard-Sørensen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
et al.:
Automating object detection and classification of foraminifera
2023
Iver Martinsen,
Benjamin Ricaud,
David Wade,
Fred Godtliebsen
:
Grouping microscopic fossils without labels using self-supervision
2023
Iver Martinsen,
Benjamin Ricaud,
David Wade,
Fred Godtliebsen
:
An efficient pipeline for microfossil analysis
2023
Steffen Aagaard Sørensen,
Eirik Myrvoll-Nilsen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
et al.:
Automated image/video classification and object detection of foraminifera
2023
David Wade,
Iver Martinsen,
Erik Anthonissen,
Alex Cullum,
Robert Williams,
Fred Godtliebsen
et al.:
Species Classification Automation for Microfossil Photomicrograph Images
2022
Iver Martinsen,
David Wade,
Fred Godtliebsen,
Benjamin Ricaud
:
SCAMPI - Species Classification Automation for Microfossil Photomicrograph Images
2022
Fred Godtliebsen,
Steffen Aagaard Sørensen,
Morten Hald
:
Automatisk overvåkning av havbunnen
Beatriz Martinez-Vega,
Eduardo Quevedo,
Raquel Leon,
Himar Fabelo,
Samuel Ortega,
Gustavo M. Callico
et al.:
Statistics-based Classification Approach for Hyperspectral Dermatologic Data Processing
2020
Phuong Ngo,
Eirik Årsand,
Fred Godtliebsen
:
Toward A Personalized Decision Support System for Blood Glucose Management During and After Physical Activities in Patients with Type 1 Diabetes
Diabetes Technology & Therapeutics 2020
FULLTEKST
Thomas Haugland Johansen,
Kajsa Møllersen,
Samuel Ortega,
Himar Fabelo,
Gustavo Callico,
Fred Godtliebsen
:
Detecting skin cancer using hyperspectral images
Advanced Science News 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
Sebastian Andres Acuña Maldonado,
G M A Mehedi Hussain,
Fred Godtliebsen,
Balpreet Singh Ahluwalia,
Hoai Phuong Ha,
Dilip K. Prasad
et al.:
Multiple Signal Classiflcation: Challenges on the Route from
Millimeter Resolution to Nanometer Resolution
2019
Phuong D. Ngo,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
2018
Phuong Ngo,
Susan Wei,
Anna Holubova,
Jan Muzik,
Fred Godtliebsen
:
Reinforcement-Learning Optimal Control for Type-1 Diabetes
Phuong D. Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
A Decision Support Tool for Optimal Control of Planet Temperature Using Reinforcement Learning
2018
Per Atle Bakkevoll,
Alexandra Makhlysheva,
Andrius Budrionis,
Taridzo Chomutare,
Line Helen Linstad,
Anne Torill Nordsletta
et al.:
Health analytics
Kunstig intelligens – nye muligheter for helsetjenesten