• Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure 

      Storås, Andrea; Riegler, Michael Alexander; Haugen, Trine B.; Thambawita, Vajira L B; Hicks, Steven Alexander; Hammer, Hugo Lewi; Kakulavarapu, Radhika; Halvorsen, Pål; Stensen, Mette Haug (Chapter; Bokkapittel, 2023-02-02)
      The in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and improve the method in the fertility clinic, the procedure is usually observed at the clinic. Alternatively, a video of the procedure can be examined and labeled in a time-consuming ...
    • Generation of synthetic tabular healthcare data using generative adversarial networks 

      Nik, Alireza Hossein Zadeh; Riegler, Michael Alexander; Halvorsen, Pål; Storås, Andrea (Chapter; Bokkapittel, 2023-03-29)
      High-quality tabular data is a crucial requirement for developing data-driven applications, especially healthcare-related ones, because most of the data nowadays collected in this context is in tabular form. However, strict data protection laws complicates the access to medical datasets. Thus, synthetic data has become an ideal alternative for data scientists and healthcare professionals to circumvent ...
    • Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence 

      Storås, Andrea; Magnø, Morten Schjerven; Fineide, Fredrik; Thiede, Bernd; Chen, Xiangjun; Strumke, Inga; Halvorsen, Pål; Utheim, Tor Paaske; Riegler, Michael Alexander; Jensen, Janicke L.; Galtung, Hilde (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-17)
      Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in ...
    • Predicting Meibomian Gland Dropout and Feature Importance Analysis with Explainable Artificial Intelligence 

      Fineide, Fredrik; Storås, Andrea; Riegler, Michael Alexander; Utheim, Tor Paaske (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-17)
      Dry eye disease is a common and potentially debilitating medical condition. Meibum secreted from the meibomian glands is the largest contributor to the outermost, protective lipid layer of the tear film. Dysfunction of the meibomian glands is the most common cause of dry eye disease. As meibomian gland dysfunction progresses, gradual atrophy of the glands is observed. The meibomian glands are ...
    • Predicting Tacrolimus Exposure in Kidney Transplanted Patients Using Machine Learning 

      Storås, Andrea; Åsberg, Anders; Halvorsen, Pål; Riegler, Michael Alexander; Strumke, Inga (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-31)
      Tacrolimus is one of the cornerstone immunosup-pressive drugs in most transplantation centers worldwide following solid organ transplantation. Therapeutic drug monitoring of tacrolimus is necessary in order to avoid rejection of the transplanted organ or severe side effects. However, finding the right dose for a given patient is challenging, even for experienced clinicians. Consequently, a tool that ...
    • Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis 

      Storås, Andrea; Andersen, Ole Emil; Lockhart, Sam; Thielemann, Roman; Gnesin, Filip; Thambawita, Vajira L B; Hicks, Steven; Kanters, Jørgen K.; Strumke, Inga; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-11)
      Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way ...
    • Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction 

      Storås, Andrea; Fineide, Fredrik; Magnø, Morten Schjerven; Thiede, Bernd; Chen, Xiangjun; Strumke, Inga; Halvorsen, Pål; Galtung, Hilde; Jensen, Janicke Cecilie Liaaen; Utheim, Tor Paaske; Riegler, Michael Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-12-22)
      Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex ...