Publications by authors named "Victor Elvira"

Article Synopsis
  • * This paper aims to create a machine learning algorithm using MRI characteristics to classify parotid gland tumors and compares its effectiveness against diagnoses made by junior and senior radiologists, incorporating data from 134 patients.
  • * The study's random forest model achieved notable accuracy (0.720) and improved diagnostic abilities for junior radiologists by 6%, suggesting the algorithm could enhance the identification of tumor types and reduce the need for invasive procedures, though further research is needed for routine implementation.
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Understanding animal movement and behaviour can aid spatial planning and inform conservation management. However, it is difficult to directly observe behaviours in remote and hostile terrain such as the marine environment. Different underlying states can be identified from telemetry data using hidden Markov models (HMMs).

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A cryogenic electrical-substitution radiometer was used for the primary calibration of monochromatic photon beams at synchrotron, which are in turn employed to determine the intrinsic efficiency of an HPGe detector between 3.5 keV and 8 keV. This allowed the determination of the thickness of the dead layer, which enabled the calculation of the efficiency up to 55 keV, where the active thickness is not determinant.

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Background And Objective: Dimethyl fumarate (DMF) is an immunomodulatory drug approved for the therapy of multiple sclerosis (MS). The identification of response biomarkers to DMF is a necessity in the clinical practice. With this aim, we studied the immunophenotypic and transcriptomic changes produced by DMF in peripheral blood mononuclear cells (PBMCs) and its association with clinical response.

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In this paper, we propose a novel and generic family of multiple importance sampling estimators. We first revisit the celebrated balance heuristic estimator, a widely used Monte Carlo technique for the approximation of intractable integrals. Then, we establish a generalized framework for the combination of samples simulated from multiple proposals.

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Background And Purpose: Limited information is available on incidence and outcomes of COVID-19 in patients with multiple sclerosis (MS). This study investigated the risks of SARS-CoV-2 infection and COVID-19-related outcomes in patients with MS, and compared these with the general population.

Methods: A regional registry was created to collect data on incidence, hospitalization rates, intensive care unit admission, and death in patients with MS and COVID-19.

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In this paper, we present order invariance theoretical results for weighted quasi-arithmetic means of a monotonic series of numbers. The quasi-arithmetic mean, or Kolmogorov-Nagumo mean, generalizes the classical mean and appears in many disciplines, from information theory to physics, from economics to traffic flow. Stochastic orders are defined on weights (or equivalently, discrete probability distributions).

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Article Synopsis
  • Markov chain Monte Carlo (MCMC) algorithms simulate complex statistical distributions through local exploration, simplifying the understanding of these distributions but potentially slowing down the overall exploration process.
  • The effectiveness of MCMC can decline as the problem's dimensions and data complexity increase, leading to a greater number of required simulations.
  • Techniques to speed up MCMC convergence include exploration strategies (like tempering and Hamiltonian Monte Carlo) and exploitation strategies (such as Rao-Blackwellization and scalable methods).
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Background: Fingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug.

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Multichannel intracavitary electrograms (EGMs) are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation. These EGMs are used by cardiologists to determine candidate areas for ablation (e.g.

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In this paper, we study a general theoretical framework which allows us to approximate the real space Ewald sum by means of effective force shifted screened potentials, together with a self term. Using this strategy it is possible to generalize the reaction field method, as a means to approximate the real space Ewald sum. We show that this method exhibits faster convergence of the Coulomb energy than several schemes proposed recently in the literature while enjoying a much more sound and clear electrostatic significance.

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