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Karl Øyvind Mikalsen
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Analysis of free text in electronic health records for identification of cancer patient trajectories
K Jensen, C Soguero-Ruiz, K Oyvind Mikalsen, RO Lindsetmo, ...
Scientific reports 7 (1), 1-12, 2017
992017
Time series cluster kernel for learning similarities between multivariate time series with missing data
KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, R Jenssen
Pattern Recognition 76, 569-581, 2018
972018
Learning representations of multivariate time series with missing data
FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen
Pattern Recognition 96, 106973, 2019
56*2019
Robust clustering using a kNN mode seeking ensemble
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Pattern Recognition 76, 491-505, 2018
422018
Noisy multi-label semi-supervised dimensionality reduction
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, R Jenssen
Pattern Recognition 90, 257-270, 2019
312019
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
AS Strauman, FM Bianchi, KØ Mikalsen, M Kampffmeyer, C Soguero-Ruiz, ...
2018 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2018
252018
Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative …
P Kocbek, N Fijacko, C Soguero-Ruiz, KØ Mikalsen, U Maver, ...
Computational and Mathematical Methods in Medicine 2019, 2019
172019
Uncertainty-aware deep ensembles for reliable and explainable predictions of clinical time series
K Wickstrøm, KØ Mikalsen, M Kampffmeyer, A Revhaug, R Jenssen
IEEE Journal of Biomedical and Health Informatics 25 (7), 2435-2444, 2020
152020
Using anchors from free text in electronic health records to diagnose postoperative delirium
KØ Mikalsen, C Soguero-Ruiz, K Jensen, K Hindberg, M Gran, ...
Computer Methods and Programs in Biomedicine 152, 105-114, 2017
122017
Learning similarities between irregularly sampled short multivariate time series from EHRs
KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, SO Skrøvseth, RO Lindsetmo, ...
112016
Mixing up contrastive learning: Self-supervised representation learning for time series
K Wickstrøm, M Kampffmeyer, KØ Mikalsen, R Jenssen
Pattern Recognition Letters 155, 54-61, 2022
72022
Time series cluster kernels to exploit informative missingness and incomplete label information
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, A Revhaug, R Jenssen
Pattern Recognition, 107896, 2021
72021
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, A Revhaug, R Jenssen
arXiv preprint arXiv:1803.07879, 2018
62018
Learning compressed representations of blood samples time series with missing data
FM Bianchi, KØ Mikalsen, R Jenssen
arXiv preprint arXiv:1710.07547, 2017
62017
Consensus clustering using knn mode seeking
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Scandinavian Conference on Image Analysis, 175-186, 2015
62015
RELAX: Representation Learning Explainability
KK Wickstrøm, DJ Trosten, S Løkse, KØ Mikalsen, MC Kampffmeyer, ...
arXiv preprint arXiv:2112.10161, 2021
22021
A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs
KØ Mikalsen, C Soguero-Ruiz, R Jenssen
Explainable AI in Healthcare and Medicine, 23-36, 2021
22021
Towards deep anchor learning
MA Hansen, KØ Mikalsen, M Kampffmeyer, C Soguero-Ruiz, R Jenssen
2018 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2018
12018
Deforming the vacuum. On the physical origin and numerical calculation of the Casimir effect.
KØ Mikalsen
UiT Norges arktiske universitet, 2014
12014
Tilgang til helseopplysninger i maskinlæringsprosjekter
MK Hauglid, KØ Mikalsen
Lov og Rett, 419-439, 2022
2022
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