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Screening outcome for interpretation by the first and second reader in a population-based mammographic screening program with independent double reading
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-28)Background - Double reading of screening mammograms is associated with a higher rate of screen-detected cancer than single reading, but different strategies exist regarding reader pairing and blinding. Knowledge about these aspects is important when considering strategies for future use of artificial intelligence in mammographic screening.<p> <p>Purpose - To investigate screening outcome, ... -
Early performance measures following regular versus irregular screening attendance in the population-based screening program for breast cancer in Norway
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-11)Irregular attendance in breast cancer screening has been associated with higher breast cancer mortality compared to regular attendance. Early performance measures of a screening program following regular versus irregular screening attendance have been less studied. We aimed to investigate early performance measures following regular versus irregular screening attendance. Methods We used information ... -
Experience of pain during mammographic screening by three different compression paddles
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-13)Introduction - Experience of pain during screening mammography is shown to affect further attendance negatively. We aimed to explore the experience of pain during screening mammography using three different breast compression paddles.<p> <p>Methods - Using a self-report questionnaire, we collected information on pain experienced during mammography from 938 women screened in Bodø at Nordland ... -
Disrupting the Social and Time Vacuum: A Systemic and Lifespan Perspective on Job Insecurity
(Journal article; Tidsskriftartikkel, 2023)In their lead article, Klug et al. conceptualize job insecurity as a multilevel construct whereby individuals are situated in meso- and macro-level contexts. Their resulting model highlights that the experience of job insecurity, as well as reactions to job insecurity, are not only affected by factors emanating from individuals' direct environment (i.e., at the individual level) but also from different ... -
The Distribution of Small-Scale Irregularities in the E-Region, and Its Tendency to Match the Spectrum of Field-Aligned Current Structures in the F-Region
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-04-16)We associate new data from icebear, a coherent scatter radar located in Saskatchewan, Canada, with scale-dependent physics in the ionosphere. We subject the large-scale icebear 3D echo patterns (treated as 2D point clouds) to a data analysis technique hitherto never applied to the ionosphere, a technique that is widely applied in cosmological red-shift surveys to characterize the spatial clustering ... -
A Mechanistic Study of the Cu-catalyzed N-arylation of Hydantoin with Aryl(TMP)iodonium Salts
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-16)The use of diaryliodonium salts in organic reactions has rapidly increased in the last decade because of their efficiency in arylation reactions. Despite this, mechanistic investigations are still scarce, particularly for copper catalyzed N-arylation reactions. Recently, we published the use of the unsymmetrical aryl(TMP)iodonium salts (TMP=2,4,6-trimethoxyphenyl) for the selective Cu-catalyzed ... -
Algorithm for predicting valvular heart disease from heart sounds in an unselected cohort
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-01-24)Objective: This study aims to assess the ability of state-of-the-art machine learning algorithms to detect valvular heart disease (VHD) from digital heart sound recordings in a general population that includes asymptomatic cases and intermediate stages of disease progression.<p> <p>Methods: We trained a recurrent neural network to predict murmurs from heart sound audio using annotated recordings ... -
Fokus på sammenhæng mellem klima, sundhed og økonomi er nødvendigt for et bæredygtigt sundhedsvæsen
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-13)Bæredygtighed indebærer at tænke langsigtet og i netværk af forbindelser, som i sidste ende har global effekt. Det skal inkluderes i de sundhedsvidenskabelige uddannelser. -
Mediating Role of Lifestyle Behaviors in the Association between Education and Cancer: Results from the European Prospective Investigation into Cancer and Nutrition
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-01-09)Background: Many studies have shown that socioeconomic position (SEP) is associated with the incidence of malignant tumors at different sites. This study aims to estimate the association between educational level (as proxy for SEP) and cancer incidence and to understand whether the observed associations might be partially explained by lifestyle behaviors.<p> <p>Methods: The analyses were performed ... -
Multiple Chemical Sensitivity: Catching up to what kind of science?
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-12-27)The recent review of Molot et al. (2023) appropriately emphasizes Multiple Chemical Sensitivity (MCS) as a growing health issue and the necessity of dedicated healthcare and medical education. The authors explain MCS mainly as the result of the sensitization of transient receptor potential (TRP) receptors, notably TRPV1 and TRPA1, and oppose this explanation to psychological processes as a causal ... -
Marine Operations in Arctic conditions
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023)Marine operations require careful early planning and thereafter detailed planning prior to project execution. The time from initiating an operation to finalization of the activity is typically several days. The activity can only be conducted during limited weather conditions. The planning prior to the offshore operations does, therefore, require accurate weather forecasting. The weather conditions ... -
AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-17)More than 38% of both screen-detected and interval cancers were assigned the highest artificial intelligence risk score on screening mammograms that preceded breast cancer diagnosis.<p> <p>Background - Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography.<p> <p>Purpose - To examine AI risk scores assigned to screening mammography in women who were ... -
Federated Partially Supervised Learning With Limited Decentralized Medical Images
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-20)Data government has played an instrumental role in securing the privacy-critical infrastructure in the medical domain and has led to an increased need of federated learning (FL). While decentralization can limit the effectiveness of standard supervised learning, the impact of decentralization on partially supervised learning remains unclear. Besides, due to data scarcity, each client may have access ... -
Strongly intermittent far scrape-off layer fluctuations in Alcator C-Mod plasmas close to the empirical discharge density limit
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-07)Intermittent plasma fluctuations in the boundary region of the Alcator C-Mod device were comprehensively investigated using data time-series from gas puff imaging and mirror Langmuir probe diagnostics. Fluctuations were sampled during stationary plasma conditions in ohmically heated, lower single null diverted configurations with scans in both line-averaged density and plasma current, with Greenwald ... -
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-22)Self-supervised learning is a central component in recent approaches to deep multi-view clustering (MVC). However, we find large variations in the development of self-supervision-based methods for deep MVC, potentially slowing the progress of the field. To address this, we present Deep-MVC, a unified framework for deep MVC that includes many recent methods as instances. We leverage our framework to ... -
Supercm: Revisiting Clustering for Semi-Supervised Learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-05)The development of semi-supervised learning (SSL) has in recent years largely focused on the development of new consistency regularization or entropy minimization approaches, often resulting in models with complex training strategies to obtain the desired results. In this work, we instead propose a novel approach that explicitly incorporates the underlying clustering assumption in SSL through extending ... -
Using a large open clinical corpus for improved ICD-10 diagnosis coding
(Journal article; Tidsskriftartikkel, 2023)With the recent advances in natural language processing and deep learning, the development of tools that can assist medical coders in ICD-10 diagnosis coding and increase their efficiency in coding discharges ummaries is significantly more viable than before. To that end, one important component in the development of these models is the datasets used to train them. In this study, such datasets are ... -
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 ... -
Optical trapping in air on a single interference fringe
(Journal article; Tidsskriftartikkel, 2023)Stable and reproducible trapping in air of 1 µm and 500 nm dielectric particles has been realized using a dual beam optical fiber tweezers with cleaved commercial single mode fibers. The influence of the interference fringes of the two coherent and counter-propagating trapping beam is investigated by controlling the fringe visibility. Optical trapping on a series of upto10 fringes or trapping on ... -
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
(Journal article; Tidsskriftartikkel, 2023)Explainable AI (XAI) is a rapidly evolving field that aims to improve transparency and trustworthiness of AI systems to humans. One of the unsolved challenges in XAI is estimating the performance of these explanation methods for neural networks, which has resulted in numerous competing metrics with little to no indication of which one is to be preferred. In this paper, to identify the most reliable ...