Viser treff 141-160 av 415

    • Deep learning neural network can measure ECG intervals and amplitudes accurately 

      Kanters, Jørgen K.; Hicks, Steven; Isaksen, Jonas L; Grarup, Niels; Holstein-Rathlou, Niels-Henrik; Ghouse, Jonas; Ahlberg, Gustav; Olesen, Morten Salling; Linneberg, Allan; Ellervik, Christina; Hansen, Torben; Graff, Claus; Halvorsen, Pål; Riegler, Michael Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-03)
    • A Generic Undo Support for State-Based CRDTs 

      Yu, Weihai; Elvinger, Victorien; Ignat, Claudia-Lavinia (Chapter; Bokkapittel, 2020-02-11)
      CRDTs (Conflict-free Replicated Data Types) have properties desirable for large-scale distributed systems with variable network latency or transient partitions. With CRDT, data are always available for local updates and data states converge when the replicas have incorporated the same updates. Undo is useful for correcting human mistakes and for restoring system-wide invariant violated due to long ...
    • Unified Power Control of Permanent Magnet Synchronous Generator Based Wind Power System with Ancillary Support during Grid Faults 

      Ramachandran, Vijayapriya; Sendraya Perumal, Angalaeswari; Lakshmaiya, Natrayan; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-10-08)
      A unified active power control scheme is devised for the grid-integrated permanent magnet synchronous generator-based wind power system (WPS) to follow the Indian electricity grid code requirements. The objective of this paper is to propose control schemes to ensure the continuous integration of WPS into the grid even during a higher percentage of voltage dip. In this context, primarily a constructive ...
    • 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 ...
    • Uncertainty Estimation and Visualization of Wind in Weather Forecasts 

      Fjukstad, Bård; Bjørndalen, John Markus; Anshus, Otto (Chapter; Bokkapittel, 2014-01)
      The Collaborative Symbiotic Weather Forecasting system, CSWF, let individual users do on-demand small region, short-term, and very high-resolution forecasts. When the regions have some overlap, a symbiotic forecast can be produced based on the individual forecasts from each region. Small differences in where the center of the region is located when there is complex terrain in the region, leads to ...
    • On evaluation metrics for medical applications of artificial intelligence 

      Hicks, Steven A.; Strumke, Inga; Thambawita, Vajira L B; Hammou, Malek; Riegler, Michael Alexander; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-08)
      Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the desirable properties of a model, which is why several metrics are typically reported to summarize a model’s performance. Unfortunately, these measures are not easily understandable by many clinicians. Moreover, comparison of models across studies ...
    • A surrogate-assisted measurement correction method for accurate and low-cost monitoring of particulate matter pollutants 

      Wojcikowski, Marek; Pankiewicz, Bogdan; Bekasiewicz, Adrian; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Vallejo, Islen; Ødegård, Rune Åvar; Ha, Hoai Phuong (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-12)
      Air pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has ...
    • WANTED! – Virtual Coach for People with Thorny Diseases 

      Halonen, Raija; Savenstedt, Stefan; Hartvigsen, Gunnar; Abächerli, Roger; Jääskeläinen, Erika; Synnes, Kåre (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-01-03)
      The main objective of this study was to propose a concept for a virtual coach to be used by people who suffer from costly and challenging diseases such as dementia, depression, diabetes and cardiac related issues, and by their caretakers presenting healthcare service providers or family members of the people suffering from the named diseases. Those listed diseases form almost an unbearable ...
    • 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. ...
    • 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. ...
    • 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.