Search results for " Neural Networks."

showing 10 items of 374 documents

A smart tele-cytology point-of-care platform for oral cancer screening.

2019

Early detection of oral cancer necessitates a minimally invasive, tissue-specific diagnostic tool that facilitates screening/surveillance. Brush biopsy, though minimally invasive, demands skilled cyto-pathologist expertise. In this study, we explored the clinical utility/efficacy of a tele-cytology system in combination with Artificial Neural Network (ANN) based risk-stratification model for early detection of oral potentially malignant (OPML)/malignant lesion. A portable, automated tablet-based tele-cytology platform capable of digitization of cytology slides was evaluated for its efficacy in the detection of OPML/malignant lesions (n = 82) in comparison with conventional cytology and hist…

MaleMedical DoctorsHealth Care ProvidersPathology and Laboratory Medicine030218 nuclear medicine & medical imaging0302 clinical medicineCohen's kappaConventional cytologyCytologyImage Processing Computer-AssistedMedicine and Health SciencesMedical PersonnelEarly Detection of CancerMultidisciplinaryOral cancer screeningQRMiddle AgedTelemedicine3. Good healthProfessionsOncology030220 oncology & carcinogenesisMedicineFemaleMouth NeoplasmsRadiologyAnatomyRisk assessmentAlgorithmsResearch ArticleComputer and Information SciencesDysplasiamedicine.medical_specialtyHistologyCytodiagnosisPoint-of-Care SystemsRemote diagnosisScienceEarly detectionRisk AssessmentSensitivity and Specificity03 medical and health sciencesSigns and SymptomsDiagnostic MedicineArtificial IntelligenceCancer Detection and DiagnosismedicineHumansArtificial Neural NetworksPoint of careComputational Neurosciencebusiness.industryBiology and Life SciencesComputational BiologyCell BiologyPathologistsHealth CarePeople and PlacesLesionsPopulation GroupingsNeural Networks ComputerCytologybusinessNeurosciencePLoS ONE
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Performance of a Predictive Model for Long-Term Hemoglobin Response to Darbepoetin and Iron Administration in a Large Cohort of Hemodialysis Patients

2016

International audience; Anemia management, based on erythropoiesis stimulating agents (ESA) and iron supplementation, has become an increasingly challenging problem in hemodialysis patients. Maintaining hemodialysis patients within narrow hemoglobin targets, preventing cycling outside target, and reducing ESA dosing to prevent adverse outcomes requires considerable attention from caregivers. Anticipation of the long-term response (i.e. at 3 months) to the ESA/iron therapy would be of fundamental importance for planning a successful treatment strategy. To this end, we developed a predictive model designed to support decision-making regarding anemia management in hemodialysis (HD) patients tr…

MalePediatricsBlood transfusionDarbepoetin alfaPhysiologymedicine.medical_treatment030232 urology & nephrologylcsh:Medicine030204 cardiovascular system & hematologyFerric CompoundsBiochemistryGlucaric AcidHemoglobinsMathematical and Statistical Techniques0302 clinical medicineMedicine and Health SciencesDarbepoetin alfaErythropoiesislcsh:ScienceFerric Oxide SaccharatedMultidisciplinaryPharmaceuticsDisease ManagementAnemia[SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/HematologyHematologyMiddle Aged3. Good healthNephrologyInjections IntravenousPhysical SciencesFemaleHemodialysisStatistics (Mathematics)Research Articlemedicine.drugComputer and Information Sciencesmedicine.medical_specialtyAnemiaResearch and Analysis Methods03 medical and health sciencesDose Prediction MethodsRenal DialysisArtificial IntelligenceMedical DialysismedicineHumansHemoglobinDosingStatistical MethodsIron Deficiency AnemiaIntensive care medicineArtificial Neural NetworksAgedRetrospective StudiesComputational NeuroscienceModels Statisticalbusiness.industrylcsh:RBiology and Life SciencesComputational BiologyProteinsRetrospective cohort studymedicine.diseaseIron-deficiency anemiaHematinicsKidney Failure ChronicCognitive Sciencelcsh:QNeural Networks ComputerHemoglobinPhysiological ProcessesbusinessMathematicsNeuroscienceForecasting
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Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI

2020

In this paper, we present an evaluation of four encoder&ndash

MaleSimilarity (geometry)Computer scienceSegNet02 engineering and technologylcsh:Chemical technologyBiochemistryArticleencoder–decoder030218 nuclear medicine & medical imagingAnalytical Chemistry03 medical and health sciencesProstate cancer0302 clinical medicineProstateImage Processing Computer-Assisted0202 electrical engineering electronic engineering information engineeringmedicineHumanslcsh:TP1-1185SegmentationElectrical and Electronic EngineeringInstrumentationmedicine.diagnostic_testPixelbusiness.industryProstateCNNsPattern recognitionMagnetic resonance imagingFCNmedicine.diseaseMagnetic Resonance ImagingU-NetAtomic and Molecular Physics and OpticsSemanticsIntensity normalizationmedicine.anatomical_structureDeepLabV3+Deep neural networks020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligencebusinessDNNSensors
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Why retail investors traded equity during the pandemic? An application of artificial neural networks to examine behavioral biases

2021

Behavioral biases are known to influence the investment decisions of retail investors. Indeed, extant research has revealed interesting findings in this regard. However, the literature on the impact of these biases on millennials' trading activity, particularly during a health crisis like the COVID-19 pandemic, as well as the equity recommendation intentions of such investors, is limited. The present study addressed these gaps by investigating the influence of eight behavioral biases: overconfidence and self-attribution, over-optimism, hindsight, representativeness, anchoring, loss aversion, mental accounting, and herding on the trading activity and recommendation intentions of millennials …

MarketingActuarial scienceMental accounting:Samfunnsvitenskap: 200::Økonomi: 210::Bedriftsøkonomi: 213 [VDP]Behavioral economicsRepresentativeness heuristicVDP::Samfunnsvitenskap: 200::Økonomi: 210Investment decisionsLoss aversionVDP::Samfunnsvitenskap: 200::Psykologi: 260detaljhandelHerdingPsychologyartificial neural networkspandemiApplied PsychologyHindsight biasOverconfidence effectPsychology & Marketing
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Dynamics of Singlet Oxygen Molecule Trapped in Silica Glass Studied by Luminescence Polarization Anisotropy and Density Functional Theory

2020

The support from M-ERANET project “MyND” is acknowledged. A.A., M.M-S., and L.R. were supported by the Research Council of Lithuania (Grant M-ERA.NET-1/2015). The authors thank A. Pasquarello for providing the structures of the amorphous SiO 2 matrix for our computational work and K. Kajihara (Tokyo Metropolitan University) for valuable advice in PL kinetics measurements.

Materials science02 engineering and technology010402 general chemistryCondensed Matter::Disordered Systems and Neural Networks7. Clean energy01 natural sciencesMolecular physicschemistry.chemical_compound:NATURAL SCIENCES:Physics [Research Subject Categories]MoleculePhysics::Chemical PhysicsPhysical and Theoretical ChemistryPolarization (electrochemistry)AnisotropySinglet oxygenDynamics (mechanics)021001 nanoscience & nanotechnology0104 chemical sciencesSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsCondensed Matter::Soft Condensed MatterGeneral EnergyPhotobiologychemistry13. Climate actionDensity functional theory0210 nano-technologyLuminescenceThe Journal of Physical Chemistry C
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Using a neural network for predicting the average grain size in friction stir welding processes

2009

In the paper the microstructural phenomena in terms of average grain size occurring in friction stir welding (FSW) processes are focused. A neural network was linked to a finite element model (FEM) of the process to predict the average grain size values. The utilized net was trained starting from experimental data and numerical results of butt joints and then tested on further butt, lap and T-joints. The obtained results show the capability of the AI technique in conjunction with the FE tool to predict the final microstructure in the FSW joints.

Materials scienceArtificial neural networkFSW metallurgy neural networksMechanical EngineeringMetallurgyMicrostructureGrain sizeFinite element methodComputer Science ApplicationsLap jointModeling and SimulationButt jointFriction stir weldingGeneral Materials ScienceFriction weldingComposite materialSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneCivil and Structural Engineering
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Mechanical and microstructural properties prediction by artificial neural networks in FSW processes of dual phase titanium alloys

2012

Abstract Friction Stir Welding (FSW), as a solid state welding process, seems to be one of the most promising techniques for joining titanium alloys avoiding a large number of difficulties arising from the use of traditional fusion welding processes. In order to pursue cost savings and a time efficient design, the development of numerical simulations of the process can represent a valid choice for engineers. In the paper an artificial neural network was properly trained and linked to an existing 3D FEM model for the FSW of Ti–6Al–4V titanium alloy, with the aim to predict both the microhardness values and the microstructure of the welded butt joints at the varying of the main process parame…

Materials scienceArtificial neural networkbusiness.industryStrategy and ManagementTitanium alloyWeldingStructural engineeringManagement Science and Operations ResearchMicrostructureIndustrial and Manufacturing EngineeringFinite element methodlaw.inventionFusion weldingFriction Stir Welding Titanium alloy Neural Networks FEMlawButt jointFriction stir weldingFriction Stir Welding Titanium alloys Neural networks FEMbusinessSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Interaction of Lamb modes with two-level systems in amorphous nanoscopic membranes

2007

Using a generalized model of interaction between a two-level system (TLS) and an arbitrary deformation of the material, we calculate the interaction of Lamb modes with TLSs in amorphous nanoscopic membranes. We compare the mean free paths of the Lamb modes with different symmetries and calculate the heat conductivity $\kappa$. In the limit of an infinitely wide membrane, the heat conductivity is divergent. Nevertheless, the finite size of the membrane imposes a lower cut-off for the phonons frequencies, which leads to the temperature dependence $\kappa\propto T(a+b\ln T)$. This temperature dependence is a hallmark of the TLS-limited heat conductance at low temperature.

Materials scienceCondensed matter physicsCondensed Matter - Mesoscale and Nanoscale PhysicsMean free pathPhononFOS: Physical sciencesConductanceDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsAmorphous solidThermal conductivityMembraneMesoscale and Nanoscale Physics (cond-mat.mes-hall)Deformation (engineering)Nanoscopic scale
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Dynamics of nanoparticles in a supercooled liquid

2008

The dynamic properties of nanoparticles suspended in a supercooled glass forming liquid are studied by x-ray photon correlation spectroscopy. While at high temperatures the particles undergo Brownian motion the measurements closer to the glass transition indicate hyperdiffusive behavior. In this state the dynamics is independent of the local structural arrangement of nanoparticles, suggesting a cooperative behavior governed by the near-vitreous solvent.

Materials scienceCondensed matter physicsDynamics (mechanics)slow dynamicsGeneral Physics and AstronomyNanoparticleX-ray scattering; glass transition; anomalous diffusion; slow dynamicsX-ray scatteringCondensed Matter::Disordered Systems and Neural NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Condensed Matter::Soft Condensed MatterSolventDynamic light scatteringChemical physicsanomalous diffusionglass transitionCooperative behaviorSupercoolingGlass transitionBrownian motion
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Secondary relaxation in the glass-transition regime of ortho-terphenyl observed by incoherent neutron scattering.

1992

We report on incoherent-neutron-scattering measurements in the supercooled regime of the van der Waals liquid ortho-terphenyl. A secondary localized relaxational process on the picosecond time scale is found. In accordance with mode-coupling theories of the glass transition, the relaxational dynamics around a critical temperature ${\mathit{T}}_{\mathit{c}}$ decomposes into two time regimes.

Materials scienceCondensed matter physicsIncoherent scatterNeutron scatteringCondensed Matter::Disordered Systems and Neural NetworksCondensed Matter::Soft Condensed Mattersymbols.namesakechemistry.chemical_compoundchemistryCritical point (thermodynamics)TerphenylPicosecondsymbolsPhysics::Chemical Physicsvan der Waals forceGlass transitionSupercoolingPhysical review. B, Condensed matter
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