Blar i NTNU Open på forfatter "Wolff, Miriam Kopperstad"

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    • Comparison of Various Insulin Pumps with Respect to Accuracy of the Insulin Delivery 

      Wolff, Miriam Kopperstad (Master thesis, 2021)
      Insulinpumper er ofte brukt som en del av behandlingen for pasienter med Diabetes Mellitus type 1. Eksisterende forskning viser at jo lavere insulindoser, jo lavere er nøyaktigheten av insulinleveransen. Dette kan være ...

    • GluPredKit: A Python Package for Blood Glucose Prediction and Evaluation 

      Wolff, Miriam Kopperstad; Royston, Sam; Volden, Rune (Journal article; Peer reviewed, 2024)
      Managing blood glucose levels is crucial for individuals with diabetes. Historically, non-linear physiological modeling of glucose dynamics laid the groundwork for automated insulin delivery. Blood glucose prediction can ...

    • GluPredKit: Development and User Evaluation of a Standardization Software for Blood Glucose Prediction 

      Wolff, Miriam Kopperstad; Royston, Sam; Fougner, Anders Lyngvi; Schaathun, Hans Georg; Steinert, Martin; Volden, Rune (Peer reviewed; Journal article, 2024)
      Blood glucose prediction is an important component of biomedical technology for managing diabetes with automated insulin delivery systems. Machine learning algorithms hold the potential to advance this technology. However, ...

    • Mobile Software Development Kit for Real Time Multivariate Blood Glucose Prediction 

      Wolff, Miriam Kopperstad; Schaathun, Hans Georg; Fougner, Anders Lyngvi; Steinert, Martin; Volden, Rune (Journal article; Peer reviewed, 2024)
      In the field of blood glucose prediction, the literature is abounded with algorithms that demonstrate potential in glucose management. However, these propositions face an issue common to many machine learning algorithms: ...

    • A Perspective on Harmonizing Diabetes Management Datasets 

      Wolff, Miriam Kopperstad; Royston, Sam; Fougner, Anders Lyngvi; Schaathun, Hans Georg; Steinert, Martin; Volden, Rune (Journal article; Peer reviewed, 2025)
      Diabetes management datasets are often compiled from various sensors and devices, including diabetes technology, activity trackers, and other health-related equipment, resulting in heterogeneous data formats. Despite the ...