Browsing by Author "Riegler, Michael Alexander"

Now showing items 21-27 of 27

    • 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 ...

    • ScopeSense: An 8.5-Month Sport, Nutrition, and Lifestyle Lifelogging Dataset 

      Riegler, Michael Alexander; Thambawita, Vajira; Chatterjee, Ayan; Nguyen, Thu; Hicks, Steven; Telle-Hansen, Vibeke; Pettersen, Svein Arne; Johansen, Dag; Jain, Ramesh; Halvorsen, Pål (Chapter; Bokkapittel, 2023-03-29)
      Nowadays, most people have a smartphone that can track their everyday activities. Furthermore, a significant number of people wear advanced smartwatches to track several vital biomarkers in addition to activity data. However, it is still unclear how these data can actually be used to improve certain aspects of people’s lives. One of the key challenges is that the collected data is often massive and ...

    • ScopeSense: An 8.5-Month Sport, Nutrition, and Lifestyle Lifelogging Dataset 

      Riegler, Michael Alexander; Thambawita, Vajira; Nguyen, Thu; Hicks, Steven Alexander; Pettersen, Svein Arne; Telle-Hansen, Vibeke; Johansen, Dag; Jain, Ramesh; Halvorsen, Pål (Journal article; Tidsskriftartikkel, 2023-03-29)
      Nowadays, most people have a smartphone that can track their everyday activities. Furthermore, a significant number of people wear advanced smartwatches to track several vital biomarkers in addition to activity data. However, it is still unclear how these data can actually be used to improve certain aspects of people’s lives. One of the key challenges is that the collected data is often massive ...

    • Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events 

      Rongved, Olav Andre Nergård; Hicks, Steven; Thambawita, Vajira L B; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06)
      Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. More specifically, event detection for soccer videos has been studied widely in the literature. However, there are still a number of shortcomings in the state-of-the-art such as high latency, making it challenging to operate at the live edge. In this paper, we present ...

    • 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 ...

    • Video Analytics in Elite Soccer: A Distributed Computing Perspective 

      Jha, Debesh; Rauniyar, Ashish; Johansen, Håvard D.; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål; Bagci, Ulas (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-22)
      Ubiquitous sensors and Internet of Things (IoT)technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post-game. New methods, including machine learning, image, and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. ...

    • Visual Sentiment Analysis from Disaster Images in Social Media 

      Zohaib Hassan, Syed; Ahmad, Kashif; Hicks, Steven; Halvorsen, Pål; Al-Fuqaha, Ala; Conci, Nicola; Riegler, Michael Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-10)
      The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on ...