Karl Øyvind Mikalsen
Karl Øyvind Mikalsen
Verifisert e-postadresse på uit.no
TittelSitert avÅr
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
372018
Analysis of free text in electronic health records for identification of cancer patient trajectories
K Jensen, C Soguero-Ruiz, KO Mikalsen, RO Lindsetmo, ...
Scientific reports 7, 46226, 2017
302017
Robust clustering using a kNN mode seeking ensemble
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Pattern Recognition 76, 491-505, 2018
152018
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
92018
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
92017
Learning similarities between irregularly sampled short multivariate time series from EHRs
KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, SO Skrøvseth, RO Lindsetmo, ...
72016
Consensus clustering using knn mode seeking
JN Myhre, KØ Mikalsen, S Løkse, R Jenssen
Scandinavian Conference on Image Analysis, 175-186, 2015
62015
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders
FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen
arXiv preprint arXiv:1805.03473, 2018
52018
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
42018
Learning compressed representations of blood samples time series with missing data
FM Bianchi, KØ Mikalsen, R Jenssen
arXiv preprint arXiv:1710.07547, 2017
42017
Noisy multi-label semi-supervised dimensionality reduction
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, R Jenssen
Pattern Recognition 90, 257-270, 2019
22019
Learning representations of multivariate time series with missing data
FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen
Pattern Recognition 96, 106973, 2019
12019
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
12019
Deforming the vacuum. On the physical origin and numerical calculation of the Casimir effect.
KØ Mikalsen
UiT Norges arktiske universitet, 2014
12014
Time series cluster kernels to exploit informative missingness and incomplete label information
KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, A Revhaug, R Jenssen
arXiv preprint arXiv:1907.05251, 2019
2019
Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare
KØ Mikalsen
UiT Norges arktiske universitet, 2019
2019
Using multi-anchors to identify patients suffering from multimorbidities
K yvind Mikalsen, C Soguero-Ruiz, I Mora-Jimenez, ICL Fando, ...
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018
2018
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
2018
The time series cluster kernel
KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, R Jenssen
2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017
2017
Deep Learning for Health
KØ Mikalsen, M Kampffmeyer, R Jenssen
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Artikler 1–20