Karl Øyvind Mikalsen

Orcid: 0000-0003-4672-7865

According to our database1, Karl Øyvind Mikalsen authored at least 29 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Exploring surgical infection prediction: A comparative study of established risk indexes and a novel model.
Int. J. Medical Informatics, 2024

Instruction-guided deidentification with synthetic test cases for Norwegian clinical text.
Proceedings of the Northern Lights Deep Learning Conference, 2024

Categorization of phenotype trajectories utilizing transformers on clinical time-series.
Proceedings of the 2024 9th International Conference on Machine Learning Technologies, 2024

2023
Selective Imputation for Multivariate Time Series Datasets With Missing Values.
IEEE Trans. Knowl. Data Eng., September, 2023

RELAX: Representation Learning Explainability.
Int. J. Comput. Vis., June, 2023

Approaching adverse event detection utilizing transformers on clinical time-series.
CoRR, 2023

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images.
Comput. Medical Imaging Graph., 2023

2022
Clinically Relevant Features for Predicting the Severity of Surgical Site Infections.
IEEE J. Biomed. Health Informatics, 2022

Mixing up contrastive learning: Self-supervised representation learning for time series.
Pattern Recognit. Lett., 2022

The Kernelized Taylor Diagram.
Proceedings of the Nordic Artificial Intelligence Research and Development, 2022

2021
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series.
IEEE J. Biomed. Health Informatics, 2021

Time series cluster kernels to exploit informative missingness and incomplete label information.
Pattern Recognit., 2021

RELAX: Representation Learning Explainability.
CoRR, 2021

On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit.
CoRR, 2021

2020
A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs.
CoRR, 2020

2019
Noisy multi-label semi-supervised dimensionality reduction.
Pattern Recognit., 2019

Learning representations of multivariate time series with missing data.
Pattern Recognit., 2019

Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data.
Comput. Math. Methods Medicine, 2019

2018
Robust clustering using a kNN mode seeking ensemble.
Pattern Recognit., 2018

Time series cluster kernel for learning similarities between multivariate time series with missing data.
Pattern Recognit., 2018

Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders.
CoRR, 2018

An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples.
CoRR, 2018

Learning compressed representations of blood samples time series with missing data.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Using multi-anchors to identify patients suffering from multimorbidities.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks.
Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics, 2018

Towards deep anchor learning.
Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics, 2018

2017
Using anchors from free text in electronic health records to diagnose postoperative delirium.
Comput. Methods Programs Biomed., 2017

The time series cluster kernel.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

2015
Consensus Clustering Using kNN Mode Seeking.
Proceedings of the Image Analysis - 19th Scandinavian Conference, 2015


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