English
norskBlar i tittel Artikler, rapporter og annet (informatikk)
Viser treff 190-209 av 389
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Metastatic Breast Cancer and Pre-Diagnostic Blood Gene Expression Profiles—The Norwegian Women and Cancer (NOWAC) Post-Genome Cohort
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-15)Breast cancer patients with metastatic disease have a higher incidence of deaths from breast cancer than patients with early-stage cancers. Recent findings suggest that there are differences in immune cell function between metastatic and non-metastatic cases, even years before diagnosis. We have analyzed whole blood gene expression by Illumina bead chips in blood samples taken using the PAXgene blood ... -
Method for Designing Semantic Annotation of Sepsis Signs in Clinical Text
(Chapter; Bokkapittel, 2023)Annotated clinical text corpora are essential for machine learning studies that model and predict care processes and disease progression. However, few studies describe the necessary experimental design of the annotation guideline and annotation phases. This makes replication, reuse, and adoption challenging. Using clinical questions about sepsis, we designed a semantic annotation guideline to ... -
Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-06)<i>Background</i>: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients’ skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but ... -
Minimizing unwanted traffic in a global messaging system. Spam, denial-of-service-attacks, and edacious subscribers
(Research report; Forskningsrapport, 2005)The main purpose of this paper is to illuminate two types of unwanted traffic in a publish/subscribe system -- malicious (spam, DoS attacks) and vain (unused events) -- and suggest a general mechanism for minimizing their effects. We do this by augmenting the classic publish/subscribe interface with volume-limiting parameters -- a combination of attributes assigned to events by publishers and ... -
ML-Peaks: Chip-seq peak detection pipeline using machine learning techniques
(Chapter; Bokkapittel, 2023-07-17)CHIP-Seq data is critical for identifying the locations where proteins bind to DNA, offering valuable insights into disease molecular mechanisms and potential therapeutic targets. However, identifying regions of protein binding, or peaks, in CHIP-seq data can be challenging due to limitations in peak detection methods. Current computational tools often require manual human inspection using data ... -
A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH
(Journal article; Tidsskriftartikkel; Peer reviewed, 2014) -
Mobile Phone-Based Pattern Recognition and Data Analysis for Patients with Type 1 Diabetes
(Journal article; Tidsskriftartikkel; Peer reviewed, 2012)Persons with type 1 diabetes who use electronic self-help tools, most commonly blood glucose meters, record a large amount of data about their personal condition. Mobile phones are powerful and ubiquitous computers that have a potential for data analysis, and the purpose of this study is to explore how self-gathered data can help users improve their blood glucose management. Thirty patients with ... -
Mobile software on mobile hardware. Experiences with TACOMA on PDAs.
(Research report; Forskningsrapport, 1997)In this paper, we present experiences from adding software mobility to mobile, hand-held computers. In particular, we have built TACOMA Lite, a mobile code system, for this environment. With TACOMA Lite installed, hand-held computers can host and execute mobile code. TACOMA Lite has been used as platform for several mobile code applications. Through experience with these applications, we have derived ... -
Model-driven diabetes care: study protocol for a randomized controlled trial
(Journal article; Tidsskriftartikkel; Peer reviewed, 2013)Background: People with type 1 diabetes who use electronic self-help tools register a large amount of information about their disease on their participating devices; however, this information is rarely utilized beyond the immediate investigation. We have developed a diabetes diary for mobile phones and a statistics-based feedback module, which we have named Diastat, to give data-driven feedback ... -
Modeling Prognostic Factors in Resectable Pancreatic Adenocarcinomas
(Journal article; Tidsskriftartikkel; Peer reviewed, 2009) -
Models for energy consumption of data structures and algorithms
(Research report; Forskningsrapport, 2014)This deliverable reports our early energy models for data structures and algorithms based on both micro-benchmarks and concurrent algorithms. It reports the early results of Task 2.1 on investigating and modeling the trade-off between energy and performance in concurrent data structures and algorithms, which forms the basis for the whole work package 2 (WP2). The work has been ... -
A Modified LeNet CNN for Breast Cancer Diagnosis in Ultrasound Images
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-24)Convolutional neural networks (CNNs) have been extensively utilized in medical image processing to automatically extract meaningful features and classify various medical conditions, enabling faster and more accurate diagnoses. In this paper, LeNet, a classic CNN architecture, has been successfully applied to breast cancer data analysis. It demonstrates its ability to extract discriminative ... -
Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-07-05)While we know that motivated students learn better than non-motivated students but detecting motivation is challenging. Here we present a game-based motivation detection approach from the EEG signals. We take an original approach of using EEG-based brain computer interface to assess if motivation state is manifest in physiological EEG signals as well, and what are suitable conditions in order to ... -
The Movitz development platform
(Research report; Forskningsrapport, 2003-12-19)We present a technical description of the Movitz development platform for stand-alone applications on the x86 PC architecture. -
Mr. Clean: A Tool for Tracking and Comparing the Lineage of Scientific Visualization Code
(Conference object; Konferansebidrag, 2014) -
MRNG: Accessing Cosmic Radiation as an Entropy Source for a Non-Deterministic Random Number Generator
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-26)Privacy and security require not only strong algorithms but also reliable and readily available sources of randomness. To tackle this problem, one of the causes of single-event upsets is the utilization of a non-deterministic entropy source, specifically ultra-high energy cosmic rays. An adapted prototype based on existing muon detection technology was used as the methodology during the experiment ... -
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-23)Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of variable sizes and train on small and biased datasets, which are common for biomedical use cases. While methods exist that incorporate multi-scale fusion approaches to address the challenges arising with variable ... -
Muithu: Smaller Footprint, Potentially Larger Imprint
(Research report; Forskningsrapport, 2012)We describe our experience with the Muithu sports notational analysis system, a novel digital information system in the popular sports domain. The system integrates real-time coach notations with related video sequences, and is configured with small, off-the shelf and cheap components. Muithu requires little or no human post-processing, which is in strong contrast to state-of-the art resource-intensive ... -
Multi-Agent Collision Avoidance Method Using Fuzzy Risk Estimation and Information Sharing in Unknown Environments
(Chapter; Bokkapittel, 2023-09-22)Automated vehicles within Industry 4.0 are used as logistics units where they can move resources from one place to another safely and efficiently. The automated vehicles can be tasked to work in unknown environments where collision-free navigation is challenging due to uncertainty and lack of environmental information. Collisions can damage equipment and may even cause harm to human workers sharing ... -
A multi-centre polyp detection and segmentation dataset for generalisability assessment
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-06)Polyps in the colon are widely known cancer precursors identifed by colonoscopy. Whilst most polyps are benign, the polyp’s number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they are not tested rigorously on a large multicentre purpose-built dataset, one reason ...
