Recent additions

  • De-identifying Swedish EHR text using public resources in the general domain 

    Chomutare, Taridzo; Yigzaw, Kassaye Yitbarek; Budrionis, Andrius; Makhlysheva, Alexandra; Godtliebsen, Fred; Dalianis, Hercules (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
    Sensitive data is normally required to develop rule-based or train machine learning-based models for de-identifying electronic health record (EHR) clinical notes; and this presents important problems for patient privacy. In this study, we add non-sensitive public datasets to EHR training data; (i) scientific medical text and (ii) Wikipedia word vectors. The data, all in Swedish, is used to train a ...
  • Challenges and opportunities beyond structured data in analysis of electronic health records 

    Tayefi, Maryam; Ngo, Phuong; Chomutare, Taridzo; Dalianis, Hercules; Salvi, Elisa; Budrionis, Andrius; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-14)
    Electronic health records (EHR) contain a lot of valuable information about individual patients and the whole population. Besides structured data, unstructured data in EHRs can provide extra, valuable information but the analytics processes are complex, time-consuming, and often require excessive manual effort. Among unstructured data, clinical text and images are the two most popular and important ...
  • Higher weight spectra of codes from Veronese threefolds 

    Johnsen, Trygve; Verdure, Hugues (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-23)
    We study binary linear codes C obtained from the quadric Veronese embedding of P<sup>3</sup> in P<sup>9</sup> over F<sub>2</sub>. We show how one can find the higher weight spectra of these codes. Our method will be a study of the Stanley-Reisner rings of a series of matroids associated to each code <i>C</i>.
  • Joint Invariants of Linear Symplectic Actions 

    Andreassen, Fredrik; Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-07)
    We review computations of joint invariants on a linear symplectic space, discuss variations for an extension of group and space and relate this to other equivalence problems and approaches, most importantly to differential invariants.
  • Differential Invariants of Linear Symplectic Actions 

    Jensen, Jørn Olav; Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-07)
    We consider the equivalence problem for symplectic and conformal symplectic group actions on submanifolds and functions of symplectic and contact linear spaces. This is solved by computing differential invariants via the Lie-Tresse theorem.
  • Vaccination criteria based on factors influencing COVID-19 diffusion and mortality 

    Spassiani, Ilaria; Gubian, Lorenzo; Palu, Giorgio; Sebastiani, Giovanni (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-15)
    SARS-CoV-2 is highly contagious, rapidly turned into a pandemic, and is causing a relevant number of critical to severe life-threatening COVID-19 patients. However, robust statistical studies of a large cohort of patients, potentially useful to implement a vaccination campaign, are rare. We analyzed public data of about 19,000 patients for the period 28 February to 15 May 2020 by several mathematical ...
  • G(3)-supergeometry and a supersymmetric extension of the Hilbert–Cartan equation 

    Kruglikov, Boris; Santi, Andrea; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-23)
    We realize the simple Lie superalgebra <i>G</i>(3) as supersymmetry of various geometric structures, most importantly super-versions of the Hilbert–Cartan equation (SHC) and Cartan's involutive PDE system that exhibit <i>G</i>(2) symmetry. We provide the symmetries explicitly and compute, via the first Spencer cohomology groups, the Tanaka–Weisfeiler prolongation of the negatively graded Lie ...
  • Hyperspectral imaging for the detection of glioblastoma tumor cells in H&E slides using convolution neural networks 

    Ortega, S.; Halicek, M.; Fabelo, H.; Camacho, R.S.; Plaza, M.L.; Godtliebsen, Fred; Callico, G. M.; Fei, Baowei (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-30)
    Hyperspectral imaging (HSI) technology has demonstrated potential to provide useful information about the chemical composition of tissue and its morphological features in a single image modality. Deep learning (DL) techniques have demonstrated the ability of automatic feature extraction from data for a successful classification. In this study, we exploit HSI and DL for the automatic differentiation ...
  • Towards detection and classification of microscopic foraminifera using transfer learning 

    Johansen, Thomas Haugland; Sørensen, Steffen Aagaard (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-02-06)
    <p>Foraminifera are single-celled marine organisms, which may have a planktic or benthic lifestyle. During their life cycle they construct shells consisting of one or more chambers, and these shells remain as fossils in marine sediments. Classifying and counting these fossils have become an important tool in e.g. oceanography and climatology. <p>Currently the process of identifying and counting ...
  • Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks 

    Bianchi, Filippo Maria; Grahn, Jakob; Eckerstorfer, Markus; Malnes, Eirik; Vickers, Hannah (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-10)
    Knowledge about frequency and location of snow avalanche activity is essential for forecasting and mapping of snow avalanche hazard. Traditional field monitoring of avalanche activity has limitations, especially when surveying large and remote areas. In recent years, avalanche detection in Sentinel-1 radar satellite imagery has been developed to improve monitoring. However, the current state-of-the-art ...
  • Estimation of Blood Glucose Concentration During Endurance Sports 

    Sebastiani, Giovanni; Uteng, Stig; Godtliebsen, Fred; Polàk, Jan; Brož, Jan (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-21)
    In this paper, we describe a new statistical approach to estimate blood glucose concentration along time during endurance sports based on measurements of glucose concentration in subcutaneous interstitial tissue. The final goal is the monitoring of glucose concentration in blood to maximize performance in endurance sports. Blood glucose concentration control during and after aerobic physical ...
  • Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling 

    Bianchi, Filippo Maria; Grattarola, Daniele; Livi, Lorenzo; Alippi, Cesare (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-31)
    In graph neural networks (GNNs), pooling operators compute local summaries of input graphs to capture their global properties, and they are fundamental for building deep GNNs that learn hierarchical representations. In this work, we propose the Node Decimation Pooling (NDP), a pooling operator for GNNs that generates coarser graphs while preserving the overall graph topology. During training, the ...
  • A polymatroid approach to generalized weights of rank metric codes 

    Ghorpade, Sudhir R; Johnsen, Trygve (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-15)
    We consider the notion of a (<i>q,m)</i>-polymatroid, due to Shiromoto, and the more general notion of (<i>q,m</i>)-demi-polymatroids, and show how generalized weights can be defined for them. Further, we establish a duality for these weights analogous to Wei duality for generalized Hamming weights of linear codes. The corresponding results of Ravagnani for Delsarte rank metric codes, and Martínez-Peñas ...
  • Relative generalized Hamming weights of affine Cartesian codes 

    Datta, Mrinmoy (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-10)
    We explicitly determine all the relative generalized Hamming weights of affine Cartesian codes using the notion of footprints and results from extremal combinatorics. This generalizes the previous works on the determination of relative generalized Hamming weights of Reed–Muller codes by Geil and Martin, as well as the determination of all the generalized Hamming weights of the affine Cartesian codes ...
  • Integrability via Geometry: Dispersionless Differential Equations in Three and Four Dimensions 

    Calderbank, David M. J.; Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-25)
    We prove that the existence of a dispersionless Lax pair with spectral parameter for a nondegenerate hyperbolic second order partial differential equation (PDE) is equivalent to the canonical conformal structure defined by the symbol being Einstein–Weyl on any solution in 3D, and self-dual on any solution in 4D. The first main ingredient in the proof is a characteristic property for dispersionless ...
  • Homogeneous Levi non-degenerate hypersurfaces in C3 

    Doubrov, Boris; Medvedev, Alexandr; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-09)
    We classify all (locally) homogeneous Levi non-degenerate real hypersurfaces in C<sup>3</sup> with symmetry algebra of dimension ≥6.
  • Blow-ups and infinitesimal automorphisms of CR-manifolds 

    Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-07)
    For a real-analytic connected CR-hypersurface M of CR-dimension n⩾1 having a point of Levi-nondegeneracy the following alternative is demonstrated for its symmetry algebra s=s(M): (i) either dims=n2+4n+3 and M is spherical everywhere; (ii) or dims⩽n2+2n+2+δ2,n and in the case of equality M is spherical and has fixed signature of the Levi form in the complement to its Levi-degeneracy locus. A version ...
  • Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data 

    Nicolau, Pedro Guilherme; Sørbye, Sigrunn Holbek; Yoccoz, Nigel (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-31)
    Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true ...
  • Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities 

    Ngo, Phuong; Tejedor Hernandez, Miguel Angel; Tayefi, Maryam; Chomutare, Taridzo; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-12)
    <p><i>Background.</i> Since physical activity has a high impact on patients with type 1 diabetes and the risk of hypoglycemia (low blood glucose levels) is significantly higher during and after physical activities, an automatic method to provide a personalized recommendation is needed to improve the blood glucose management and harness the benefits of physical activities. This paper aims to reduce ...
  • Generalized eigenvalue methods for Gaussian quadrature rules 

    Blekherman, Grigoriy; Kummer, Mario; Riener, Cordian; Schweighofer, Markus; Vinzant, Cynthia (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
    A quadrature rule of a measure <i>µ</i> on the real line represents a conic combination of finitely many evaluations at points, called nodes, that agrees with integration against <i>µ</i> for all polynomials up to some fixed degree. In this paper, we present a bivariate polynomial whose roots parametrize the nodes of minimal quadrature rules for measures on the real line. We give two symmetric ...

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