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Author Albiol, A.; Albiol, F.; Paredes, R.; Plasencia-Martinez, J.M.; Blanco Barrio, A.; Garcia Santos, J.M.; Tortajada, S.; Gonzalez Montano, V.M.; Rodriguez Godoy, C.E.; Fernandez Gomez, S.; Oliver-Garcia, E.; de la Iglesia Vaya, M.; Marquez Perez, F.L.; Rayo Madrid, J.I.
Title A comparison of Covid-19 early detection between convolutional neural networks and radiologists Type Journal Article
Year 2022 Publication Insights into Imaging Abbreviated Journal Insights Imaging
Volume 13 Issue 1 Pages 122 - 12pp
Keywords Deep learning; Covid-19; Radiology
Abstract Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19.
Address [Albiol, Alberto] Univ Politecn Valencia, iTeam Inst, ETSI Telecomunicac, Camino Vera S-N, Valencia 46022, Spain, Email: alalbiol@iteam.upv.es
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1869-4101 ISBN Medium
Area Expedition Conference
Notes WOS:000832727200003 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial (down) 5302
Permanent link to this record
 

 
Author Mandal, S.; Miranda, O.G.; Sanchez Garcia, G.; Valle, J.W.F.; Xu, X.J.
Title High-energy colliders as a probe of neutrino properties Type Journal Article
Year 2022 Publication Physics Letters B Abbreviated Journal Phys. Lett. B
Volume 829 Issue Pages 137110 - 5pp
Keywords
Abstract The mediators of neutrino mass generation can provide a probe of neutrino properties at the next round of high-energy hadron (FCC-hh) and lepton colliders (FCC-ee/ILC/CEPC/CLIC). We show how the decays of the Higgs triplet scalars mediating the simplest seesaw mechanism can shed light on the neutrino mass scale and mass-ordering, as well as the atmospheric octant. Four-lepton signatures at the high-energy frontier may provide the discovery-site for charged lepton flavor non-conservation in nature, rather than low-energy intensity frontier experiments.
Address [Mandal, Sanjoy] Korea Inst Adv Study, Seoul 02455, South Korea, Email: smandal@kias.re.kr;
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0370-2693 ISBN Medium
Area Expedition Conference
Notes WOS:000831681800020 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial (down) 5301
Permanent link to this record
 

 
Author Rinaldi, M.; Ceccopieri, F.A.; Vento, V.
Title The pion in the graviton soft-wall model: phenomenological applications Type Journal Article
Year 2022 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 82 Issue 7 Pages 626 - 18pp
Keywords
Abstract The holographic graviton soft-wall model, introduced to describe the spectrum of scalar and tensor glueballs, is improved to incorporate the realization of chiral-symmetry as in QCD. Such a goal is achieved by including the longitudinal dynamics of QCD into the scheme. Using the relation between AdS/QCD and light-front dynamics, we construct the appropriate wave function for the pion which is used to calculate several pion observables. The comparison of our results with phenomenology is remarkably successful.
Address [Rinaldi, Matteo] Univ Perugia, Ist Nazl Fis Nucl, Dipartimento Fis & Geol, Sect Perugia, Via A Pascoli, I-06123 Perugia, Italy, Email: matteo.rinaldi@pg.infn.it
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:000828534300001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial (down) 5300
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Author LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J.
Title Precision measurement of forward Z boson production in proton-proton collisions at root s=13 TeV Type Journal Article
Year 2022 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 07 Issue 7 Pages 026 - 57pp
Keywords Electroweak Interaction; Forward Physics; Hadron-Hadron Scattering; Particle and Resonance Production
Abstract A precision measurement of the Z boson production cross-section at root s = 13 TeV in the forward region is presented, using pp collision data collected by the LHCb detector, corresponding to an integrated luminosity of 5.1 fb(-1). The production cross-section is measured using Z -> mu(+)mu(-) events within the fiducial region defined as pseudorapidity 2.0 < eta < 4.5 and transverse momentum p(T) > 20 GeV/c for both muons and dimuon invariant mass 60 < M-mu μ< 120 GeV/c(2). The integrated cross-section is determined to be sigma(Z -> mu(+)mu(-)) = 196.4 +/- 0.2 +/- 1.6 +/- 3.9 pb, where the first uncertainty is statistical, the second is systematic, and the third is due to the luminosity determination. The measured results are in agreement with theoretical predictions within uncertainties.
Address [de Souza Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Falcao, L. N.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: hang.yin@cern.ch
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1029-8479 ISBN Medium
Area Expedition Conference
Notes WOS:000825333400003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial (down) 5299
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Author Roser, J.; Barrientos, L.; Bernabeu, J.; Borja-Lloret, M.; Muñoz, E.; Ros, A.; Viegas, R.; Llosa, G.
Title Joint image reconstruction algorithm in Compton cameras Type Journal Article
Year 2022 Publication Physics in Medicine and Biology Abbreviated Journal Phys. Med. Biol.
Volume 67 Issue 15 Pages 155009 - 15pp
Keywords Compton camera; compton imaging; hadron therapy; image reconstruction; LM-MLEM; Monte Carlo simulations; multi-layer compton telescope
Abstract Objective. To demonstrate the benefits of using an joint image reconstruction algorithm based on the List Mode Maximum Likelihood Expectation Maximization that combines events measured in different channels of information of a Compton camera. Approach. Both simulations and experimental data are employed to show the algorithm performance. Main results. The obtained joint images present improved image quality and yield better estimates of displacements of high-energy gamma-ray emitting sources. The algorithm also provides images that are more stable than any individual channel against the noisy convergence that characterizes Maximum Likelihood based algorithms. Significance. The joint reconstruction algorithm can improve the quality and robustness of Compton camera images. It also has high versatility, as it can be easily adapted to any Compton camera geometry. It is thus expected to represent an important step in the optimization of Compton camera imaging.
Address [Roser, J.; Barrientos, L.; Bernabeu, J.; Borja-Lloret, M.; Munoz, E.; Ros, A.; Viegas, R.; Llosa, G.] CSIC UV, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Jorge.Roser@ific.uv.es
Corporate Author Thesis
Publisher IOP Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-9155 ISBN Medium
Area Expedition Conference
Notes WOS:000827830200001 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial (down) 5298
Permanent link to this record