Search results for "NEURAL NETWORKS"

showing 10 items of 599 documents

Prediction of bone mass gain by bone turnover parameters after parathyroidectomy for primary hyperparathyroidism: neural network software statistical…

2006

Background Primary hyperparathyroidism (pHPT) is the most frequent endocrine hypersecretion disease, and parathyroidectomy is the only curative option, since pharmacologic therapy reduces hypercalcemia but does not impede parathyroid hormone hypersecretion. According to guidelines from the National Institutes of Health, parathyroidectomy is associated with bone mass increase in some asymptomatic patients, while in others bone mass is not changed after surgery. Therefore, we performed the present study in an attempt to elucidate whether a preoperative biochemical bone parameter can be predictive of a significant vertebral bone mass increase in patients with pHPT. Methods For each patient we …

Parathyroidectomymedicine.medical_specialtymedicine.medical_treatmentUrinary systemUrologyParathyroid hormoneCollagen Type Ibone mass bone mineralization bone turnoverBone remodelingBone DensityHumansMedicineAgedAged 80 and overParathyroidectomyHyperparathyroidismbiologybusiness.industryMiddle AgedHyperparathyroidism Primarymedicine.diseaseUrinary calciumSurgeryOsteocalcinbiology.proteinSurgeryBone RemodelingNeural Networks ComputerPeptidesbusinessPrimary hyperparathyroidismSurgery
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Search for standard model Higgs bosons produced in association with W bosons.

2007

We report on the results of a search for standard model Higgs bosons produced in association with W bosons from p-pbar collisions at root s = 1.96 TeV. The search uses a data sample corresponding to approximately 1 fb-1 of integrated luminosity. Events consistent with the W to l-nu and H to b-bbar signature are selected by triggering on a high-pT electron or muon candidate and tagging one or two of the jet candidates as having originated from b quarks. A neural network filter rejects a fraction of tagged charm and light flavor jets, increasing the b-jet purity in the sample and thereby reducing the background to Higgs boson production. We observe no excess l-nu-b-bbar production beyond the …

Particle physicsFOS: Physical sciencesNeural network filtersGeneral Physics and AstronomyElementary particleddc:500.201 natural sciencesStandard ModelHigh Energy Physics - ExperimentNuclear physicsHigh Energy Physics - Experiment (hep-ex)13.85.Rm 14.80.BnJets0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Mass hypothesesSampling010306 general physicsBosonsBosonPhysicsProblem solvingMathematical models010308 nuclear & particles physicsBranching fractionPhysicsHigh Energy Physics::PhenomenologyCenter (category theory)Higgs BosonsHiggs bosonProduction (computer science)High Energy Physics::ExperimentNeural networksLeptonPhysical review letters
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SELDI-TOF-MS ProteinChip array profiling of tears from patients with dry eye.

2005

Protein and peptides in tears play an important role in ocular surface diseases. In previous studies, changes have been demonstrated in the electrophoretic protein profiles of patients with dry eye. The purpose of this work was to determine the usefulness of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) ProteinChip Array (Ciphergen Biosystems, Inc., Fremont, CA) technology for the automated analysis of proteins and peptides in tear fluid.Patients with dry eye (DRY, n = 88) and healthy subjects (CTRL, n = 71) were examined. Their tear proteins were analyzed using SELDI-TOF-MS ProteinChip Arrays with three different chromatographic surfaces (CM10…

Pathologymedicine.medical_specialtyEye diseaseProtein Array AnalysisDry Eye SyndromesLipocalinchemistry.chemical_compoundSELDI-TOF-MSmedicineHumansIn patientEye ProteinsChromatography High Pressure LiquidChromatographybusiness.industryHealthy subjectsmedicine.diseaseChromatography Ion ExchangechemistrySpectrometry Mass Matrix-Assisted Laser Desorption-IonizationTearsTearsDry Eye SyndromesNeural Networks ComputerLysozymebusinessPeptidesBiomarkersInvestigative ophthalmologyvisual science
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Percolation and Schramm–Loewner evolution in the 2D random-field Ising model

2011

Abstract The presence of random fields is well known to destroy ferromagnetic order in Ising systems in two dimensions. When the system is placed in a sufficiently strong external field, however, the size of clusters of like spins diverges. There is evidence that this percolation transition is in the universality class of standard site percolation. It has been claimed that, for small disorder, a similar percolation phenomenon also occurs in zero external field. Using exact algorithms, we study ground states of large samples and find little evidence for a transition at zero external field. Nevertheless, for sufficiently small random-field strengths, there is an extended region of the phase d…

Percolation critical exponentsRandom fieldStatistical Mechanics (cond-mat.stat-mech)Schramm–Loewner evolutionCondensed matter physicsFOS: Physical sciencesGeneral Physics and AstronomyPercolation thresholdDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksDirected percolationHardware and ArchitecturePercolationIsing modelContinuum percolation theoryStatistical physicsCondensed Matter - Statistical MechanicsMathematicsComputer Physics Communications
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Prospective study of sport dropout: A motivational analysis as a function of age and gender

2012

Abstract Introduction: This paper aimed to analyse the predictive ability of a self-determination theory (SDT) based model describing competitive sport dropout, and variance as a function of age and gender. Variables included in the model were: psychological need satisfaction, self-determined motivation, perceived conflict between sport and study, intention to practise sport, and dropout. Methods: A prospective study was performed over a period of 19 months. Variables considered as predictors of sport dropout were measured initially, and after 19 months persistence or dropout was assessed. The sample consisted of 857 athletes aged 11–19 (mean value 15.3; standard deviation = 1.77), 680 male…

Persistence (psychology)biologyAthletesPhysical Therapy Sports Therapy and RehabilitationSample (statistics)General MedicineVariance (accounting)biology.organism_classificationStandard deviationStructural equation modelingDevelopmental psychologyOrthopedics and Sports MedicineProspective cohort studyPsychologyDropout (neural networks)European Journal of Sport Science
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Drugs and Nondrugs:  An Effective Discrimination with Topological Methods and Artificial Neural Networks

2003

A set of topological and structural descriptors has been used to discriminate general pharmacological activity. To that end, we selected a group of molecules with proven pharmacological activity including different therapeutic categories, and another molecule group without any activity. As a method for pharmacological activity discrimination, an artificial neural network was used, dividing molecules into active and inactive, to train the network and externally validate it. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval, and the output value of the neural network versus these values. Pharmacological distribution diagram…

PharmacologyArtificial neural networkChemistryComputer scienceValue (computer science)Biological activityGeneral MedicineGeneral ChemistryInterval (mathematics)Function (mathematics)TopologyPlot (graphics)Computer Science ApplicationsSet (abstract data type)Structure-Activity RelationshipPharmaceutical PreparationsComputational Theory and MathematicsDiscriminative modelData DisplayNeural Networks ComputerInformation SystemsJournal of Chemical Information and Computer Sciences
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The Prediction of Human Intestinal Absorption Based on the Molecular Structure

2014

Human Intestinal Absorption (HIA) has been modeled many times by using classification models. However, regression models are scarce. Here, Artificial Neural Networks (ANNs) are implemented for this purpose. A dataset of structurally diverse chemicals with their respective experimental HIA were used to design robust, true predictive and widespread applicable ANN models. An input variables pool was made up of structural invariants calculated by using either Dragon or our software Desmol 1. The selection of best variables was performed following three steps using the entire dataset of molecules. Firstly, variables poorly correlated with the experimental data were eliminated. Secondly, input va…

Pharmacologyeducation.field_of_studyMolecular StructureArtificial neural networkComputer sciencebusiness.industryClinical BiochemistryPopulationReproducibility of ResultsPattern recognitionFeature selectionRegression analysisModels TheoreticalBackpropagationIntestinal absorptionIntestinal AbsorptionPharmaceutical PreparationsResamplingTest setHumansNeural Networks ComputerArtificial intelligenceeducationbusinessCurrent Drug Metabolism
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Critical and tricritical singularities of the three-dimensional random-bond Potts model for large $q$

2005

We study the effect of varying strength, $\delta$, of bond randomness on the phase transition of the three-dimensional Potts model for large $q$. The cooperative behavior of the system is determined by large correlated domains in which the spins points into the same direction. These domains have a finite extent in the disordered phase. In the ordered phase there is a percolating cluster of correlated spins. For a sufficiently large disorder $\delta>\delta_t$ this percolating cluster coexists with a percolating cluster of non-correlated spins. Such a co-existence is only possible in more than two dimensions. We argue and check numerically that $\delta_t$ is the tricritical disorder, which se…

Phase transitionCondensed matter physicsSpinsStatistical Mechanics (cond-mat.stat-mech)FOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter::Disordered Systems and Neural NetworksPhase (matter)Cluster (physics)Gravitational singularityCritical exponentRandomnessCondensed Matter - Statistical MechanicsPotts modelMathematics
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Dielectric polarization in PLZT X/65/35 and PbMg1/3Nb2/3O3at the diffuse phase transition

1992

Abstract The transformation of the hysteresis loops in PLZT x/65/35 in the region of diffuse phase transition is discussed in relation to the behaviour of dielectric permittivity. The Vogel-Fulcher type dielectric relaxation is used to describe the discussed phenomena.

Phase transitionMaterials scienceCondensed matter physicsDielectric permittivityPhysics::OpticsRelative permittivityDielectricCondensed Matter PhysicsCondensed Matter::Disordered Systems and Neural NetworksElectronic Optical and Magnetic MaterialsDielectric spectroscopyCondensed Matter::Materials ScienceHysteresisRelaxation (physics)Cole–Cole equationFerroelectrics
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Computer simulation of models for orientational glasses

1991

Abstract Monte Carlo studies of two- and three-dimensional lattice models where quadrupoles interact with a nearest-neighbor Gaussian coupling are reviewed. None of these models has a thermodynamic glass phase transition at non-zero temperature like the Ising spin glass: rather, phase transitions at zero temperature occur that exhibit a dynamical freeze-in spread out over a wide temperature range and are characterized by a strongly non-exponential relaxation. The time-dependent glass order parameter, q(t), decays with time, t, compatible with a stretched exponential decay q(t) ∼ exp [− (t/τ)y] with a strongly temperature-dependent exponent. While the static glass ‘susceptibility’ for isotro…

Phase transitionMaterials scienceCondensed matter physicsIsotropyAtmospheric temperature rangeCondensed Matter PhysicsCondensed Matter::Disordered Systems and Neural NetworksElectronic Optical and Magnetic MaterialsExponential functionLattice (order)Materials ChemistryCeramics and CompositesExponentExponential decayCritical dimensionJournal of Non-Crystalline Solids
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