Now showing items 41-60 of 251

    • MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies 

      Inguanzo, Anna; Poulakis, Konstantinos; Mohanty, Rosaleena; Schwarz, Christopher G.; Przybelski, Scott A.; Diaz-Galvan, Patricia; Lowe, Val J.; Boeve, Bradley F.; Lemstra, Afina W.; van de Beek, Marleen; van der Flier, Wiesje; Barkhof, Frederik; Blanc, Frederic; Loureiro de Sousa, Paulo; Philippi, Nathalie; Cretin, Benjamin; Demuynck, Catherine; Nedelska, Zuzana; Hort, Jakub; Segura, Barbara; Junque, Carme; Oppedal, Ketil; Aarsland, Dag; Westman, Eric; Kantarci, Kejal; Ferreira, Daniel (Peer reviewed; Journal article, 2023)
      Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) ...
    • Kernel recursive least squares dictionary learning algorithm 

      Alipoor, Ghasem; Skretting, Karl (Peer reviewed; Journal article, 2023)
      An online dictionary learning algorithm for kernel sparse representation is developed in the current paper. In this framework, the input signal nonlinearly mapped into the feature space is sparsely represented based on a ...
    • Recurrent Neural Networks for Artifact Correction in HRV Data During Physical Exercise 

      Svane, Jakob; Wiktorski, Tomasz; Ørn, Stein; Eftestøl, Trygve Christian (Peer reviewed; Journal article, 2023)
      In this paper, we propose the use of recurrent neural networks (RNNs) for artifact correction and analysis of heart rate variability (HRV) data. HRV can be a valuable metric for determining the function of the heart and ...
    • A Low-Cost Wireless Body Area Network for Human Activity Recognition in Healthy Life and Medical Applications 

      Demrozi, Florenc (Peer reviewed; Journal article, 2023)
      Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more ...
    • Resource Allocation in Networking and Computing Systems: A Security and Dependability Perspective 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023)
      In recent years, there has been a trend to integrate networking and computing systems, whose management is getting increasingly complex. Resource allocation is one of the crucial aspects of managing such systems and is ...
    • Prostate Age Gap: An MRI Surrogate Marker of Aging for Prostate Cancer Detection 

      Fernandez Quilez, Alvaro; Nordström, Jon Tobias; Jäderling, Fredrik; Kjosavik, Svein Reidar; Eklund, Martin (Peer reviewed; Journal article, 2023)
      Background Aging is the most important risk factor for prostate cancer (PC). Imaging techniques can be useful to measure age-related changes associated with the transition to diverse pathological states. However, biomarkers ...
    • Making sense of nonsense : Integrated gradient-based input reduction to improve recall for check-worthy claim detection 

      Sheikhi, Ghazaal; Opdahl, Andreas Lothe; Touileb, Samia; Setty, Vinay (CEUR Workshop Proceedings;, Chapter, 2023)
      Analysing long text documents of political discourse to identify check-worthy claims (claim detection) is known to be an important task in automated fact-checking systems, as it saves the precious time of fact-checkers, ...
    • Mitigating non-linear DAC glitches using dither in closed-loop nano-positioning applications 

      Faza, Ahmad Mohammad Ahmad; Leth, John; Eielsen, Arnfinn Aas (American Control COnference (ACC);, Chapter, 2023)
      Digital-to-analog conversion is essential in digital signal processing applications, including closed-loop control schemes. Noise and distortion in digital-to-analog converters result in reduced performance for high-precision ...
    • Detection and localization of melanoma skin cancer in histopathological whole slide images 

      Kanwal, Neel; Amundsen, Roger; Hardardottir, Helga; Tomasetti, Luca; Undersrud, Erling Sandøy; Janssen, Emiel; Engan, Kjersti (European Signal Processing Conference;, Chapter; Conference object, 2023)
      If melanoma is diagnosed and treated in its early stages can increase the survival rate. A projected increase in skin cancer incidents and a shortage of dermatopathologists have emphasized the need for computational pathology ...
    • An XAI approach for COVID-19 detection using transfer learning with X-ray images 

      Sarp, Salih; Catak, Ferhat Özgur; Kuzlu, Murat; Cali, Umit; Kusetogullari, Huseyin; Zhao, Yanxiao; Guler, Ozgur (Peer reviewed; Journal article, 2023-04)
      The coronavirus disease (COVID-19) has continued to cause severe challenges during this unprecedented time, affecting every part of daily life in terms of health, economics, and social development. There is an increasing ...
    • A Practical Implementation of Medical Privacy-Preserving Federated Learning Using Multi-Key Homomorphic Encryption and Flower Framework 

      Walskaar, Ivar; Tran, Minh Christian; Catak, Ferhat Özgur (Peer reviewed; Journal article, 2023-10)
      The digitization of healthcare data has presented a pressing need to address privacy concerns within the realm of machine learning for healthcare institutions. One promising solution is federated learning, which enables ...
    • 5G-MEC Testbeds for V2X Applications 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023-05)
      Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low ...
    • Structural identifiability of biomolecular controller motifs with and without flow measurements as model output 

      Haus, Eivind Sandve; Drengstig, Tormod; Thorsen, Kristian (Peer reviewed; Journal article, 2023-08)
      Controller motifs are simple biomolecular reaction networks with negative feedback. They can explain how regulatory function is achieved and are often used as building blocks in mathematical models of biological systems. ...
    • Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction 

      Svane, Jakob; Wiktorski, Tomasz; Trygve Christian, Eftestøl; Stein, Ørn (Peer reviewed; Journal article, 2023-09)
      Heart rate variability (HRV) is the variation in time between successive heartbeats and can be used as an indirect measure of autonomic nervous system (ANS) activity. During physical exercise, movement of the measuring ...
    • Interval Type 2 Fuzzy Adaptive Motion Drive Algorithm Design 

      Ali, Syed M.; Guo, Yanling; Rizvi, Syed Tahir Hussain; Amin, Roohul; Yasin, Awais (Peer reviewed; Journal article, 2023-07)
      Motion drive algorithms are a set of filters designed to simulate realistic motion and are an integral part of contemporary vehicle simulators. This paper presents the design of a novel intelligent interval type 2 fuzzy ...
    • Automated Diagnosis of Prostate Cancer Using mpMRI Images: A Deep Learning Approach for Clinical Decision Support 

      Gavade, Anil B.; Nerli, Rajendra; Kanwal, Neel; Gavade, Priyanka A.; Pol, Shridhar Sunilkumar; Rizvi, Syed Tahir Hussain (Peer reviewed; Journal article, 2023)
      Prostate cancer (PCa) is a significant health concern for men worldwide, where early detection and effective diagnosis can be crucial for successful treatment. Multiparametric magnetic resonance imaging (mpMRI) has evolved ...
    • Transforming spatio-temporal self-attention using action embedding for skeleton-based action recognition 

      Ahmad, Tasweer; Rizvi, Syed Tahir Hussain; Kanwal, Neel (Peer reviewed; Journal article, 2023-09)
      Over the past few years, skeleton-based action recognition has attracted great success because the skeleton data is immune to illumination variation, view-point variation, background clutter, scaling, and camera motion. ...
    • An Extensible Framework for Implementing and Validating Byzantine Fault-tolerant Protocols 

      Gogada, Hanish; Jehl, Leander; Meling, Hein; Olsen, John Ingve (Chapter, 2023-06)
      HotStuff is a Byzantine fault-tolerant state machine replication protocol that incurs linear communication costs to achieve consensus. This linear scalability promoted the protocol to be adopted as the consensus mechanism ...
    • Cost-effective Data Upkeep in Decentralized Storage Systems 

      Nygaard, Racin Wilhelm; Meling, Hein; Olsen, John Ingve (Conference object; Journal article, 2023)
      Decentralized storage systems split files into chunks and distribute the chunks across a network of peers. Each peer may only store a few chunks per file. To later reconstruct a file, all its chunks must be downloaded. ...
    • Trustworthy journalism through AI 

      Opdahl, Andreas Lothe; Tessem, Bjørnar; Dang Nguyen, Duc Tien; Motta, Enrico; Setty, Vinay; Throndsen, Eivind; Tverberg, Are; Trattner, Christoph (Peer reviewed; Journal article, 2023-07)
      Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid ...