Viser treff 221-240 av 483

    • 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 ...
    • Statistical supervised learning with engineering data: a case study of low frequency noise measured on semiconductor devices 

      Gámiz, María Luz; Kalén, Anton; Nozal Cañadas, Rafael; Raya-Miranda, Rocío (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-04)
      Our practical motivation is the analysis of potential correlations between spectral noise current and threshold voltage from common on-wafer MOSFETs. The usual strategy leads to the use of standard techniques based on Normal linear regression easily accessible in all statistical software (both free or commercial). However, these statistical methods are not appropriate because the assumptions they ...
    • Virtual Power Plants and Integrated Energy System: Current Status and Future Prospects 

      Mishra, Sambeet; Bordin, Chiara; Leinakse, Madis; Wen, Fushuan; J. Howlett, Robert; Palu, Ivo (Chapter; Bokkapittel, 2022)
      The power system is undergoing a digitalization, decarbonization, and decentralization. Economic incentives along with resiliency and reliability concerns are partly driving the transition. In the process of decentralization, local energy markets are forming at various places. A virtual power plant (VPP) is a by-product of this digitalization capitalizing on the opportunity to further promote renewable ...
    • Polar Vantage and Oura Physical Activity and Sleep Trackers: Validation and Comparison Study 

      Henriksen, André; Grimsgaard, Sameline; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-27)
      Background: Consumer-based activity trackers are increasingly used in research, as they have the potential to promote increased physical activity and can be used for estimating physical activity among participants. However, the accuracy of newer consumer-based devices is mostly unknown, and validation studies are needed.<p> <p>Objective: The objective of this study was to compare the Polar Vantage ...
    • Kvik: three-tier data exploration tools for flexible analysis of genomic data in epidemiological studies [version 1; peer review: 2 approved with reservations] 

      Fjukstad, Bjørn; Olsen, Karina Standahl; Jareid, Mie; Lund, Eiliv; Bongo, Lars Ailo (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-03-30)
      Kvik is an open-source system that we developed for explorative analysis of functional genomics data from large epidemiological studies. Creating such studies requires a significant amount of time and resources. It is therefore usual to reuse the data from one study for several research projects. Often each project requires implementing new analysis code, integration with specific knowledge bases, ...
    • Information and communication technology-based interventions for chronic diseases consultation: Scoping review 

      Randine, Pietro; Sharma, Aakash; Hartvigsen, Gunnar; Johansen, Håvard D.; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-29)
      Background: Medical consultations are often critical meetings between patients and health personnel to provide treatment, health-management advice, and exchange of information, especially for people living with chronic diseases. The adoption of patient-operated Information and Communication Technologies (ICTs) allows the patients to actively participate in their consultation and treatment. The ...
    • On Optimizing Transaction Fees in Bitcoin using AI: Investigation on Miners Inclusion Pattern 

      Tedeschi, Enrico; Nordmo, Tor-Arne Schmidt; Johansen, Dag; Johansen, Håvard D. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-09)
      The transaction-rate bottleneck built into popular proof-of-work-based cryptocurrencies, like Bitcoin and Ethereum, leads to fee markets where transactions are included according to a first-price auction for block space. Many attempts have been made to adjust and predict the fee volatility, but even well-formed transactions sometimes experience unexpected delays and evictions unless a substantial ...
    • Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge 

      Ross, Tobias; Reinke, Annika; M. Full, Peter; Wagner, Martin; Kenngott, Hannes; Apitz, Martin; Hempe, Hellena; Mindroc Filimon, Diana; Scholz, Patrick; Tran, Thuy Nuong; Bruno, Pierangela; Arbeláez, Pablo; Bian, Gui-Bin; Bodenstedt, Sebastian; Lindström Bolmgren, Jon; Bravo-Sánchez, Laura; Chen, Hua-Bin; González, Cristina; Guo, Dong; Halvorsen, Pål; Heng, Pheng-Ann; Hosgor, Enes; Hou, Zeng-Guang; Isensee, Fabian; Jha, Debesh; Jiang, Tingting; Jin, Yueming; Kirtac, Kadir; Kletz, Sabrina; Leger, Stefan; Li, Zhixuan; H. Maier-Hein, Klaus; Ni, Zhen-Liang; Riegler, Michael; Schoeffmann, Klaus; Shi, Ruohua; Speidel, Stefanie; Stenzel, Michael; Twick, Isabell; Wang, Gutai; Wang, Jiacheng; Wang, Liansheng; Wang, Lu; Zhang, Yujie; Zhou, Yan-Jie; Zhu, Lei; Wiesenfarth, Manuel; Kopp-Schneider, Annette; P. Müller-Stich, Beat; Maier-Hein, Lena (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-28)
      Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and roboticassisted interventions. While numerous methods for detecting, segmenting and tracking of medical instruments based on endoscopic video images have been proposed in the literature, key limitations remain to be addressed: Firstly, robustness, that is, the reliable performance of state-of-the-art methods ...