English
norskBlar i forfatter "Mikalsen, Karl Øyvind"
Viser treff 21-25 av 25
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Tilgang til helseopplysninger i maskinlæringsprosjekter (antatt, kommende)
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-14)Artikkelen tar for seg reglene for tilgang til helseopplysninger med utgangspunkt i behovene som foreligger i prosjekter der forskere, utviklere eller andre ønsker å behandle opplysningene ved hjelp av maskinlæring. Spørsmål om behandlingsgrunnlag, formålsbegrensning og dataminimering etter GDPR drøftes, før den norske helselovgivningens bestemmelser om tilgang til helseopplysninger analyseres. Både ... -
Time series cluster kernel for learning similarities between multivariate time series with missing data
(Journal article; Tidsskriftartikkel; Peer reviewed, 2017-12-06)<p>Similarity-based approaches represent a promising direction for time series analysis. However, many such methods rely on parameter tuning, and some have shortcomings if the time series are multivariate (MTS), due to dependencies between attributes, or the time series contain missing data. In this paper, we address these challenges within the powerful context of kernel methods by proposing the ... -
Time series cluster kernels to exploit informative missingness and incomplete label information
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-20)The time series cluster kernel (TCK) provides a powerful tool for analysing multivariate time series subject to missing data. TCK is designed using an ensemble learning approach in which Bayesian mixture models form the base models. Because of the Bayesian approach, TCK can naturally deal with missing values without resorting to imputation and the ensemble strategy ensures robustness to hyperparameters, ... -
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-07)Deep learning-based support systems have demonstrated encouraging results in numerous clinical applications involving the processing of time series data. While such systems often are very accurate, they have no inherent mechanism for explaining what influenced the predictions, which is critical for clinical tasks. However, existing explainability techniques lack an important component for trustworthy ... -
Using anchors from free text in electronic health records to diagnose postoperative delirium
(Journal article; Tidsskriftartikkel; Peer reviewed, 2017-09-19)Objectives:<br> Postoperative delirium is a common complication after major surgery among the elderly. Despite its potentially serious consequences, the complication often goes undetected and undiagnosed. In order to provide diagnosis support one could potentially exploit the information hidden in free text documents from electronic health records usin ...
