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norskBlar i tittel Artikler, rapporter og annet (informatikk)
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Data Analysis Techniques for Smart Nudging
(Conference object; Konferansebidrag, 2021)<p>Nudge principles and techniques are significant in communications, marketing, and groups’ motivation to improve personal health, wealth, and well-being. We make numerous decisions in online situations. People’s health and well-being have garnered widespread interest and concern in this wearable’s age. Smart nudging is defined as “digital nudging, where the guidance of user behavior is tailored ... -
Data collection and analysis methods for smart nudging to promote physical activity: Protocol for a mixed methods study
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023)New digital technologies like activity trackers, nudge concepts, and approaches can inspire and improve personal health. There is increasing interest in employing such devices to monitor people’s health and well-being. These devices can continually gather and examine health-related information from people and groups in their familiar surroundings. Context-aware nudges can assist people in self-managing ... -
Data collection and smart nudging to promote physical activity and a healthy lifestyle using wearable devices
(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 ... -
Data-Driven and Artificial Intelligence (AI) Approach for Modelling and Analyzing Healthcare Security Practice: A Systematic Review
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03)Data breaches in healthcare continue to grow exponentially, calling for a rethinking into better approaches of security measures towards mitigating the menace. Traditional approaches including technological measures, have significantly contributed to mitigating data breaches but what is still lacking is the development of the “human firewall,” which is the conscious care security practices of the ... -
Data-driven blood glucose pattern classification and anomalies detection: Machine-learning applications in Type 1 diabetes
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019-05-01)<p><i>Background - </i>Diabetes mellitus is a chronic metabolic disorder that results in abnormal blood glucose (BG) regulations. The BG level is preferably maintained close to normality through self-management practices, which involves actively tracking BG levels and taking proper actions including adjusting diet and insulin medications. BG anomalies could be defined as any undesirable reading ... -
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-26)<i>Background</i>: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabetes. However, self-management of the disease, especially keeping BG in the recommended range, is central to the treatment. This includes actively ... -
Data-intensive computing infrastructure systems for unmodified biological data analysis pipelines
(Journal article; Tidsskriftartikkel; Peer reviewed, 2015-11-18)Biological data analysis is typically implemented using a deep pipeline that combines a wide array of tools and databases. These pipelines must scale to very large datasets, and consequently require parallel and distributed computing. It is therefore important to choose a hardware platform and underlying data management and processing systems well suited for processing large datasets. There are many ... -
Dataset of Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-03-01)Physical activity (PA) data were downloaded from 113 participants who owned a Garmin or Fitbit activity tracker in 2019 and 2020. Upon participant authorization, data were automatically downloaded from the Garmin and Fitbit cloud storages. The mSpider tool, a solution for automatic and continuous data extraction from activity tracker providers, were used to download participant data. Available ... -
Dataset of fitness trackers and smartwatches to measuring physical activity in research
(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 ... -
Dataset of motivational factors for using mobile health applications and systems
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-16)We created and carried out a cross-sectional anonymous structured questionnaire on what motivates users of mobile health applications and wearables to share their collected health related data. The questionnaire was distributed online in English, French, and Norwegian. In addition, a flyer with information of where to locate the online questionnaire was distributed during a Swiss health conference. ... -
De-identifying Norwegian Clinical Text using Resources from Swedish and Danish
(Journal article; Tidsskriftartikkel, 2023)The lack of relevant annotated datasets represents one key limitation in the application of Natural Language Processing techniques in a broad number of tasks, among them Protected Health Information (PHI) identification in Norwegian clinical text. In this work, the possibility of exploiting resources from Swedish, a very closely related language, to Norwegian is explored. The Swedish dataset is ... -
A Declarative Profile Model for Qos negotiation
(Research report; Forskningsrapport, 2005-12)In this report we define the semantics of a language for dynamic QoS expressions which can be evaluated at run-time for conformance. We define how expressions can be constructed from atomic expressions termed ’basic profiles’ using composition operators. Two such operators are defined: The sum ( ’+’ ) which corresponds to simple conjunction and component-sum (’Å’) which assume that the operands ... -
A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-09)An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data are presented as images, identifying properties that characterize a disease becomes far more challenging. A common strategy involves extracting features from the images and ... -
Deep learning and hand-crafted feature based approaches for polyp detection in medical videos
(Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-23)Video analysis including classification, segmentation or tagging is one of the most challenging but also interesting topics multimedia research currently try to tackle. This is often related to videos from surveillance cameras or social media. In the last years, also medical institutions produce more and more video and image content. Some areas of medical image analysis, like radiology or brain ... -
Deep Learning for Enhanced Fault Diagnosis of Monoblock Centrifugal Pumps: Spectrogram-Based Analysis
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-31)Abstract The reliable operation of monoblock centrifugal pumps (MCP) is crucial in various industrial applications. Achieving optimal performance and minimizing costly downtime requires effectively detecting and diagnosing faults in critical pump components. This study proposes an innovative approach that leverages deep transfer learning techniques. An accelerometer was adopted to capture vibration ... -
Deep learning neural network can measure ECG intervals and amplitudes accurately
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-03) -
Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources
(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 ... -
Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024)This study discusses the methods and challenges of deidentifying and pseudonymizing Norwegian clinical text for research purposes. The results of the NorDeid tool for deidentification and pseudonymization on different types of protected health information were evaluated and discussed, as well as the extension of its functionality with regular expressions to identify specific types of sensitive ... -
DeltaTree: A Locality-aware Concurrent Search Tree
(Journal article; Tidsskriftartikkel; Peer reviewed, 2015-06-15)Like other fundamental abstractions for high-performance computing, search trees need to support both high concurrency and data locality. However, existing locality-aware search trees based on the van Emde Boas layout (vEB-based trees), poorly support concurrent (update) operations. We present DeltaTree, a practical locality-aware concurrent search tree that integrates both locality-optimization ... -
DeltaTree: A Practical Locality-aware Concurrent Search Tree
(Research report; Forskningsrapport, 2013)As other fundamental programming abstractions in energy-e cient computing, search trees are expected to support both high parallelism and data locality. However, existing highly-concurrent search trees such as red-black trees and AVL trees do not consider data locality while existing locality-aware search trees such as those based on the van Emde Boas layout (vEB-based trees), poorly support ...
