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), 46226, 2017
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
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
Learning representations of multivariate time series with missing data
FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen
Pattern Recognition 96, 106973, 2019
Robust clustering using a kNN mode seeking ensemble
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Pattern Recognition 76, 491-505, 2018
Noisy multi-label semi-supervised dimensionality reduction
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, R Jenssen
Pattern Recognition 90, 257-270, 2019
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
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
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 (1), 2059851, 2019
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
Learning similarities between irregularly sampled short multivariate time series from EHRs
KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, SO Skrøvseth, RO Lindsetmo, ...
Relax: Representation learning explainability
KK Wickstrøm, DJ Trosten, S Løkse, A Boubekki, K Mikalsen, ...
International Journal of Computer Vision, 1-27, 2023
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
KK Wickstrøm, EA Østmo, K Radiya, KØ Mikalsen, MC Kampffmeyer, ...
Computerized Medical Imaging and Graphics 107, 102239, 2023
Performance and clinical applicability of machine learning in liver computed tomography imaging: a systematic review
K Radiya, HL Joakimsen, KØ Mikalsen, EK Aahlin, RO Lindsetmo, ...
European Radiology 33 (10), 6689-6717, 2023
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
Selective imputation for multivariate time series datasets with missing values
A Blázquez-García, K Wickstrøm, S Yu, KØ Mikalsen, A Boubekki, ...
IEEE Transactions on Knowledge and Data Engineering 35 (9), 9490-9501, 2023
Learning compressed representations of blood samples time series with missing data
FM Bianchi, KØ Mikalsen, R Jenssen
arXiv preprint arXiv:1710.07547, 2017
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
Consensus clustering using knn mode seeking
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark …, 2015
AI risk score on screening mammograms preceding breast cancer diagnosis
M Larsen, CF Olstad, HW Koch, MA Martiniussen, SR Hoff, ...
Radiology 309 (1), e230989, 2023
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