Search results for "machine learning."

showing 10 items of 1455 documents

Reliability Generalization Meta-Analysis

2020

Un meta-análisis de generalización de confiabilidad (MA GF) es un método para integrar estadísticamente las estimaciones de fiabilidad obtenidas en diferentes aplicaciones de un test. El MA GF permite a los investigadores caracterizar la fiabilidad promedio de las puntuaciones obtenida en un test en múltiples estudios y situaciones y estimar el grado de variabilidad en los coeficientes de fiabilidad en diferentes tipos de medidas, muestras y contextos. Por lo tanto, sus resultados permiten ofrecer pautas a los investigadores y profesionales aplicados sobre qué escalas son más fiables para evaluar un constructo y en qué circunstancias. Así pues, los investigadores y profesionales necesitan s…

Psychological testsGeneralizationComputer scienceCalidad de la investigaciónMachine learningcomputer.software_genreCoeficiente de fiabilidadNeed to knowGeneralización de la fiabilidadReliability (statistics)Meta-análisisbusiness.industryResearch qualityEvidence-based psychologyReliability generalizationTest (assessment)Meta-analysisCritical appraisalTests psicológicosPersonalidad Evaluación y Tratamiento PsicológicoCritical readingReliability coefficientArtificial intelligencebusinesscomputerPsicología basada en la evidenciaINFORMACIÓ PSICOLÒGICA
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The Post-COVID-19 Functional Status scale: a tool to measure functional status over time after COVID-19

2020

Since the outbreak of the Coronavirus disease 2019 (COVID-19) pandemic, most attention has focused on containing transmission of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and addressing the surge of critically ill patients in acute care settings. Indeed, as of April 29th 2020, over 3 million confirmed cases have been accounted for globally [1]. In the coming weeks and months, emphasis will gradually involve also post-acute care of COVID-19 survivors. It is anticipated that COVID-19 may have a major impact on physical, cognitive, mental and social health status, also in patients with mild disease presentation [2]. Previous outbreaks of coronaviruses have been associate…

Pulmonary and Respiratory Medicine2019-20 coronavirus outbreakActivities of daily livingCoronavirus disease 2019 (COVID-19)Scale (ratio)IMPACTPneumonia ViralMeasure (physics)610 Medicine & healthMachine learningcomputer.software_genreDiagnostic Self EvaluationBetacoronavirusDiagnostic Self Evaluation03 medical and health sciences0302 clinical medicineSurveys and QuestionnairesActivities of Daily LivingCorrespondenceHumansMedicinePatient Reported Outcome Measures030212 general & internal medicinePandemicsCOVIDSARS-CoV-2business.industry10031 Clinic for AngiologyCOVID-19Recovery of FunctionPhysical Functional Performance030228 respiratory system2740 Pulmonary and Respiratory MedicineQuality of LifeFunctional statusArtificial intelligenceCoronavirus InfectionsbusinesscomputerCoronavirus Infections
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The EU-funded I3LUNG Project:Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy

2023

Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a major challenge, as programmed Death-Ligand 1 (PD-L1) is currently the only biomarker used to predict the outcome of IO in NSCLC patients despite its limited efficacy. Considering the dynamic complexity of the immune system-tumor microenvironment (TME) and its interaction with the host's and patient's behavior, it is unlikely that a single biomarker will accurately predict a patient's outcomes. …

Pulmonary and Respiratory MedicineCancer ResearchArtificial intelligenceOncologyNon-small cell lung cancerPredictive biomarkersMachine learningPersonalized medicine
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Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective …

2022

Item does not contain fulltext BACKGROUND: Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. METHODS: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifie…

Pulmonary and Respiratory MedicineClinical SciencesAcute Lung InjuryArticleMachine LearningPositive-Pressure RespirationRare DiseasesClinical ResearchRetrospective StudieSettore MED/41 - ANESTESIOLOGIAHumansLungAcute Respiratory Distress SyndromeRetrospective StudiesRespiratory Distress SyndromeOther Medical and Health SciencesLUNG SAFE Investigators and the ESICM Trials Grouplnfectious Diseases and Global Health Radboud Institute for Health Sciences [Radboudumc 4]PhenotypeGood Health and Well BeingArea Under CurveARDS: PhenotypeRespiratoryPublic Health and Health ServicesARDSHuman
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Is a 1-cm margin from major vessels adequate for radiofrequency ablation of pulmonary neoplasms?

2009

Pulmonary and Respiratory Medicinemedicine.medical_specialtybusiness.industryMargin (machine learning)Radiofrequency ablationlawPulmonary neoplasmsMedicineSurgeryRadiologyCardiology and Cardiovascular Medicinebusinesslaw.invention
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Hierarchical Syntactic Models for Human Activity Recognition through Mobility Traces

2019

AbstractRecognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known asgrammatical inference. We also introduce a measure ofsimilaritythat accounts for the intrinsic hierarchical nature of su…

QA75Computer science02 engineering and technologyManagement Science and Operations ResearchSimilarity measureMachine learningcomputer.software_genreZA4050Set (abstract data type)Activity recognitionGrammatical inference Human activity recognition Mobility020204 information systemsSmart citySimilarity (psychology)0202 electrical engineering electronic engineering information engineeringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFinite-state machineT1business.industryGrammar inductionComputer Science ApplicationsHardware and Architecture020201 artificial intelligence & image processingArtificial intelligenceGranularitybusinesscomputer
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Continuous Analysis of Running Mechanics by Means of an Integrated INS/GPS Device

2019

This paper describes a single body-mounted sensor that integrates accelerometers, gyroscopes, compasses, barometers, a GPS receiver, and a methodology to process the data for biomechanical studies. The sensor and its data processing system can accurately compute the speed, acceleration, angular velocity, and angular orientation at an output rate of 400 Hz and has the ability to collect large volumes of ecologically-valid data. The system also segments steps and computes metrics for each step. We analyzed the sensitivity of these metrics to changing the start time of the gait cycle. Along with traditional metrics, such as cadence, speed, step length, and vertical oscillation, this system est…

QA75GV557_SportsT1neuroverkotlcsh:Chemical technologyneural networksArticlejuoksumachine learningkoneoppiminenmittauslaitteetsatelliittipaikannusMachine learninggait analysislcsh:TP1-1185sports equipmentbiomekaniikkaINS/GPSvelocity measurement
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Instruction-based clinical eye-tracking study on the visual interpretation of divergence : how do students look at vector field plots?

2018

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux concept. We test the effectiveness of both strategies in an instruction-based eye-tracking study with N = 41 physics majors. We found that students’ performance improved when both strategies were introduced (74% correct) instead of only one strategy (64% correct), and students performed best when they were free to choose between the two strategies (88…

QC1-999graafinen esitysUndergraduate StudentsPhysics Education ResearchGeneral Physics and AstronomyResearch MethodologyContext (language use)LernenAssessmentMachine learningcomputer.software_genre01 natural sciencesEducationVisual processingsilmänliikkeetddc:370Concept learning0103 physical sciencesvektorit (matematiikka)ddc:530ta516Wissensrepräsentation010306 general physicsDivergence (statistics)graphical representationsvisual processingeye-trackingLC8-6691studentsopiskelijatbusiness.industryPhysicsMultimethodology05 social sciencesConcepts & Principles050301 educationKognitives LernenSpecial aspects of educationSaccadic maskingPhysikdidaktikEye trackingPartial derivativeArtificial intelligencebusinessvector fields0503 educationcomputer
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Application of machine-vision techniques to fish-quality assessment

2012

Abstract Machine vision is a non-destructive, rapid, economic, consistent and objective inspection tool and is also an evaluation technique based on image analysis and processing with a variety of applications. We review the use of machine vision and imaging technologies for fish-quality assessment. This review updates and condenses a representative selection of recent research and industrial solutions proposed in order to evaluate the general trends of machine vision and image processing in the visible range applied for inspection of fish and fish products. In order to determine freshness and composition, it is necessary to measure and to evaluate size and volume, to estimate weight, to me…

Quality assessmentComputer scienceMachine visionbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFish speciesColor analysisImage processingMachine learningcomputer.software_genreFish qualityAbstract machineAnalytical ChemistryVisible rangeArtificial intelligencebusinesscomputerSpectroscopyComputingMethodologies_COMPUTERGRAPHICSTrAC Trends in Analytical Chemistry
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Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

2017

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector…

Quantitative structure–activity relationshipAntiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringModes of toxic action010501 environmental sciencesMachine learningcomputer.software_genre01 natural sciencesMachine Learningchemistry.chemical_compoundPhenolsMolecular descriptorDrug DiscoveryPhenols0105 earth and related environmental sciencesCiliated protozoanArtificial neural networkbusiness.industryTetrahymena pyriformisGeneral Medicine0104 chemical sciencesSupport vector machine010404 medicinal & biomolecular chemistrychemistryTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerbusinesscomputerSAR and QSAR in environmental research
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