Viser treff 241-260 av 707

    • Standards for reporting randomized controlled trials in medical informatics: a systematic review of CONSORT adherence in RCTs on clinical decision support 

      Augestad, Knut Magne; Berntsen, Gro; Lassen, Kristoffer; Bellika, Johan Gustav; Wootton, Richard; Lindsetmo, Rolv-Ole (Journal article; Tidsskriftartikkel; Peer reviewed, 2011-07-29)
      Introduction The Consolidated Standards for Reporting Trials (CONSORT) were published to standardize reporting and improve the quality of clinical trials. The objective of this study is to assess CONSORT adherence in randomized clinical trials (RCT) of disease specific clinical decision support (CDS).<p> <p>Methods A systematic search was conducted of the Medline, EMBASE, and Cochrane databases. ...
    • Non-Opportunistic Data Transfer for IoT and Cyber-Physical Systems with Mostly Sleeping Nodes 

      Hellemo, Isak Østrem (Mastergradsoppgave; Master thesis, 2022-07-12)
      Sensor networks are frequently used to monitor our environment. From monitoring the habitat of seabirds [1], to the structural integrity of bridges [2]. They can also be used to monitor the arctic tundra to help us monitor climate change. The arctic tundra does however place additional requirements on a monitoring system. Low access to energy sources, human intervention, and networks to transfer ...
    • Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources 

      Eide, Siri Sofie; Riegler, Michael; Hammer, Hugo Lewi; Bremnes, John Bjørnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-06)
      Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them via a late fusion based approach. To tackle this challenge, we develop and investigate the usefulness of a novel deep learning method called tower networks. This method is able ...
    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile loss, a popular loss function in quantile regression, to monitor the quantile tracking error, which, in turn, is used to efficiently adapt to concept drift. The suggested ...
    • Towards a New Model for Chronic Disease Consultations 

      Randine, Pietro; Cooper, John Graham; Hartvigsen, Gunnar; Årsand, Eirik (Chapter; Bokkapittel, 2022-08-22)
      Medical consultations for chronic diseases form an arena to provide information from health personnel to patients. This information is necessary for patients to understand how to deal with the possible lifelong symptoms and needed self-management activities. The amount of patient-generated health data is increasing. Today’s patients gather an increasing amount of personalised health-related information. ...
    • Social media, physical activity and autism: better or bitter together? A scoping review 

      Gabarron, Elia; Henriksen, André; Nordahl-Hansen, Anders (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-22)
      This review provides an overview of the existing research on social media, autism, and physical activity. We searched for publications on PubMed, PsycInfo, Embase, Education source, ERIC, IEEE Xplore, and the proceedings from conferences on health informatics and autism. Eight studies were included in this review. Studies reported mixed results on the link between social media, physical activity, ...
    • Ubiquitous digital health-related data: clarification of concepts 

      Johannessen, Erlend; Henriksen, André; Hartvigsen, Gunnar; Horsch, Alexander; Årsand, Eirik; Johansson, Jonas (Chapter; Bokkapittel, 2022-08-22)
      The increased development and use of ubiquitous digital services reinforce the trend where health-related data is generated everywhere. Data usage in different areas introduces different terms for the same or similar concepts. This adds to the confusion of what these terms represent. We aim to provide an overview of concepts and terms used in connection with digital twins and in a healthcare context.
    • Predictive analytics beyond time series: Predicting series of events extracted from time series data 

      Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; Purkayastha, Adri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-07)
      Realizing carbon neutral energy generation creates the challenge of accurately predicting time-series generation data for long-term capacity planning and for short-term operational decisions. The key challenges for adopting data-driven decision-making, specifically predictive analytics, can be attributed to data volume and velocity. Data volume poses challenges for data storage and retrieval. Data ...
    • Expectations of users and non-users of wearable sensors and mobile health applications 

      Henriksen, André; Pfuhl, Gerit; Woldaregay, Ashenafi Zebene; Issom, David-Zacharie; Årsand, Eirik; Sato, Keiichi; Hartvigsen, Gunnar (Chapter; Bokkapittel, 2022-08-22)
      Patient self-management is vital to improved health outcomes for patients with chronic diseases. The objective of this study was to understand the role of wearable sensors in patients’ self-management. A survey encompassing factors related to motivation in mHealth was conducted. Ease of use and sensory accuracy was found most important when choosing a wearable. Manual registration of most health-related ...
    • Designing an e-Health Program for Lifestyle Changes in Diabetes Care A Qualitative Pre-Study in Norway 

      Rishaug, Tina; Henriksen, André; Aas, Anne-Marie; Hartvigsen, Gunnar; Birkeland, Kåre Inge; Årsand, Eirik (Chapter; Bokkapittel, 2022-08-22)
      Type 2 diabetes mellitus (T2D) and prediabetes prevalence rates are high. Consequences are serious, but current treatment is often not efficient for achieving remission. Remission may be achieved through lifestyle intervention. Frequent follow-up is necessary, and health care personnel (HCP) lack resources, time, and often adequate knowledge. Self-management of T2D can benefit from better use of ...
    • Data collection and smart nudging to promote physical activity and a healthy lifestyle using wearable devices 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne; Henriksen, André (Chapter; Bokkapittel, 2022-08-22)
      Nudge principles and techniques can motivate and improve personal health through emerging digital devices, such as activity trackers. Tracking people's health and well-being using such devices have earned widespread interest. These devices can continuously capture and analyze health-related data from individuals and communities in their everyday environment. Providing context-aware nudges can help ...
    • Proceedings of the 18th Scandinavian Conference on Health Informatics 

      Henriksen, André; Gabarron, Elia; Vimarlund, Vivian (Book; Bok, 2022-08-22)
      This proceeding presents the papers presented at the 18th Scandinavian Conference on Health Informatics - SHI 2022 in Tromsø, Norway on August 22-24, 2022.
    • Smart contract formation enabling energy-as-a-service in a virtual power plant 

      Mishra, Sambeet; John Crasta, Cletus; Bordin, Chiara; Mateo‐Fornés, Jordi (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-22)
      Energy as a service (EaaS) is an emerging business model that enables the otherwise passive energy consumers to play an active role and participate in the energy utility services. This platform is formed through smart contracts registering peer-to-peer (P2P) transactions of energy through price and quantity. Many industries, including finance, have already leveraged smart contracts to introduce ...
    • Resilient expansion planning of virtual power plant with an integrated energy system considering reliability criteria of lines and towers 

      Bordin, Chiara; Mishra, Sambeet; Wu, Qiuwei; Manninen, Henri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-25)
      The portfolio of virtual power plants (VPP) is a flexible system for facilitating a wide range of resources with wide geographical coverage. A VPP can be placed at the intersection of electric power and energy systems by adding heat pumps to the portfolio, thereby accelerating the formation of integrated energy systems. VPPs, while virtual, still rely on a physical network for operations. The power ...
    • Áika: A Distributed Edge System for AI Inference 

      Alslie, Joakim Aalstad; Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-17)
      Video monitoring and surveillance of commercial fisheries in world oceans has been proposed by the governing bodies of several nations as a response to crimes such as overfishing. Traditional video monitoring systems may not be suitable due to limitations in the offshore fishing environment, including low bandwidth, unstable satellite network connections and issues of preserving the privacy of crew ...
    • Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering 

      Liu, Zicheng; Roy, Mayank; Prasad, Dilip K.; Agarwal, Krishna (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-03-15)
      Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost. Recently, deep neural network (DNN) techniques have been successfully applied on ISPs and shown potential of superior imaging over conventional methods. In this paper, we discuss techniques for effective incorporation of important physical ...
    • Dataset of fitness trackers and smartwatches to measuring physical activity in research 

      Henriksen, André; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-16)
      Objectives: Accelerometer-based wrist-worn ftness trackers and smartwatches (wearables) appeared on the consumer market in 2011. Many wearable devices have been released since. The objective of this data paper is to describe a dataset of 423 wearables released before July 2017.<p> <p>Data description: We identifed wearables and extracted information from six online and ofine databases. We ...
    • End-to-end Trainable Ship Detection in SAR Images with Single Level Features 

      Tiller, Markus (Master thesis; Mastergradsoppgave, 2022-06-01)
      Kongsberg Satellite Services (KSAT) use machine learning and manual analysis done by synthetic aperture radar (SAR) specialists on SAR images in real time to provide a ship detection service. KSATs current machine learning model has a limited ability to distinguish ships close to each other. For this reason, we aim to employ an end-to-end trainable object detection model, as they can better ...
    • Investigating and developing efficient federated learning for air pollution monitoring 

      Reinnes, Jørgen (Master thesis; Mastergradsoppgave, 2022-06-01)
      Location-based data may be considered highly private; as such, handling location-based data requires that it cannot be used to track a user. In a network of multiple edge devices that each collect data, training a machine learning model would typically involve transmitting the data securely to a central server which requires strict privacy rules. Federated learning solves the privacy problem ...
    • Correctness Criteria for Function-Based Reclassifiers: A Language Based Approach 

      Hansen, Steinar Brenna (Master thesis; Mastergradsoppgave, 2022-06-01)
      An emerging problem in systems security is controlling how a program uses the data it has access to. Information Flow Control (ifc) propagates restrictions on data by following the flow of information, for example if a secret value flows to a public value, that value should be considered secret as well. A common problem in ifc is reclassification of data, for instance to explicitly make data ...