Search results for "Predictive model"

showing 10 items of 74 documents

Tumor lysis syndrome in patients with acute myeloid leukemia: identification of risk factors and development of a predictive model

2008

Background Despite the prophylactic use of allopurinol, tumor lysis syndrome (TLS)- related morbidity and mortality still occur in a number of patients with acute myeloid leukemia (AML).The aim of this study was: (i) to analyze the incidence and outcome of TLS in a large series of patients with AML receiving hyperhydration and allopurinol, (ii) to identify risk factors for TLS, and (iii) to develop a prognostic scoring system for estimating individual risk of TLS. Design and Methods The study included 772 adult patients with AML receiving induction chemotherapy between 1980 and 2002. TLS was divided into laboratory TLS (LTLS) or clinical TLS (CTLS).The population study was randomly divided …

OncologyAdultMalemedicine.medical_specialtyMyeloidAdolescentAntineoplastic Agentsacute myeloid leukemiapredictive modelRisk FactorsInternal medicinemedicineRasburicaseHumansrisk factorsRisk factorAgedNeoplasm StagingAged 80 and overHematologybusiness.industryMyeloid leukemiaInduction chemotherapyHematologyMiddle Agedmedicine.diseasePrognosisTumor lysis syndromeLeukemiaLeukemia Myeloid Acutemedicine.anatomical_structureTreatment OutcomeImmunologyincidenceFemaletumor lysis syndromebusinessTumor Lysis Syndromemedicine.drug
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Technical Note: Prediction Models of Airborne Sound Insulation of Multilayer Materials with Viscoelastic Thin Sheets

2008

The growing introduction of new insulation materials in building acoustics has caused an increase of the importance of the prediction tools. Appropriate simulations allow strictly necessary laboratory measurements to be identified. In this way, costs are reduced. The demands of new legislation has resulted in the appearance of various software designed to facilitate prediction. The prediction models are based on different hypotheses: adaptation of impedances, spatial behaviour of spectral components, statistical energy distribution, the Finite Element Method (FEM), etc. Each of these models and methods offer advantages and contain limitations. In this paper, different models for prediction…

Acoustics and UltrasonicsComputer sciencebusiness.industryMechanical EngineeringAcousticsMechanical engineeringTechnical noteBuilding and ConstructionViscoelasticityFinite element methodSoundproofingSoftwarebusinessAdaptation (computer science)Electrical impedancePredictive modellingBuilding Acoustics
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Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing

2018

International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…

0209 industrial biotechnologyDesignComputer sciencecomputer.internet_protocol02 engineering and technologycomputer.software_genreBayesian inferenceIndustrial and Manufacturing EngineeringArticle[SPI]Engineering Sciences [physics]020901 industrial engineering & automationPMML0202 electrical engineering electronic engineering information engineeringanalyticsUncertainty quantificationMonte-Carlouncertaintycomputer.programming_languageParsingBayesian networkInformationSystems_DATABASEMANAGEMENTstandardPython (programming language)XMLComputer Science ApplicationsmanufacturingComputingMethodologies_PATTERNRECOGNITIONBayesian networksControl and Systems EngineeringSurface-RoughnessData analysisPredictive Model Markup Language020201 artificial intelligence & image processingData miningcomputerXML
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Probabilité d'apparition d'un phénomène parasitaire et choix de modèles de régression logistique

2007

Epidemiological processes are now using spatial statistics and modelling tools. The main objective of most health risks studies consists in identifying potential contamination sources and factors capable of explaining their localization. Health data often prove binary (typically presence/absence) and specific methods such as binary logistic regression have to be used. This method's output consists in a probability for the pathogen of interest. A posterior classification of each sample is then conducted using a probability threshold. The method used to maximize this threshold is called the ROC curve which consists in giving a representation of the behaviour of the model and then to choose th…

Spatial epidemiology Binary logistic regression ROC curves Predictive modelling[SHS.GEO] Humanities and Social Sciences/Geography[SHS.GEO]Humanities and Social Sciences/GeographyÉpidémiologie spatiale Régression logistique binaire Courbes ROC Modélisation prédictive[ SHS.GEO ] Humanities and Social Sciences/Geography
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Towards the improvement of food flavour analysis: Modelling chemical and sensory data and expert knowledge integration

2019

International audience

[SDV.AEN] Life Sciences [q-bio]/Food and Nutritionmixture of odorantsfood flavorexpert knowledgefuzzy logicpredictive modelling[SDV.AEN]Life Sciences [q-bio]/Food and NutritionComputingMilieux_MISCELLANEOUSolfaction
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Dynamic mean absolute error as new measure for assessing forecasting errors

2018

Abstract Accurate wind power forecast is essential for grid integration, system planning, and electricity trading in certain electricity markets. Therefore, analyzing prediction errors is a critical task that allows a comparison of prediction models and the selection of the most suitable model. In this work, the temporal error and absolute magnitude error are simultaneously considered to assess the forecast error. The trade-off between both types of errors is computed, analyzed, and interpreted. Moreover, a new index, the dynamic mean absolute error, DMAE, is defined to measure the prediction accuracy. This index accounts for both error components: temporal and absolute. Real cases of wind …

Absolute magnitudeWind powerIndex (economics)Renewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industry020209 energyWork (physics)Energy Engineering and Power Technology02 engineering and technology021001 nanoscience & nanotechnologyGridMeasure (mathematics)Fuel TechnologyNuclear Energy and EngineeringStatistics0202 electrical engineering electronic engineering information engineeringElectricity0210 nano-technologybusinessPredictive modellingEnergy Conversion and Management
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Development Of An Econometric Model Case Study: Romanian Classification System

2015

Abstract The purpose of the paper is to illustrate an econometric model used to predict the lean meat content in pig carcasses, based on the muscle thickness and back fat thickness measured by the means of an optical probe (OptiGrade PRO).The analysis goes through all steps involved in the development of the model: statement of theory, specification of the mathematical model, sampling and collection of data, estimation of the parameters of the chosen econometric model, tests of the hypothesis derived from the model and prediction equations. The data have been in a controlled experiment conducted by the Romanian Carcass Classification Commission in 2007. The purpose of the experiment was to …

EstimationStatement (computer science)HF5001-6182Social PsychologyInterviewComputer scienceEconomics Econometrics and Finance (miscellaneous)seurop systemSampling (statistics)Regression analysiseconometricsregression analysispredictive modelEconometric modelEconometricsBusiness Management and Accounting (miscellaneous)Normativemedia_common.cataloged_instanceBusinessEuropean unioneconometrics predictive model regression analysis SEUROP systemmedia_commonStudies in Business and Economics
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Macrophytes in boreal streams: Characterizing and predicting native occurrence and abundance to assess human impact

2016

Abstract Macrophytes are a structurally and functionally essential element of stream ecosystems and therefore indispensable in assessment, protection and restoration of streams. Modelling based on continuous environmental gradients offers a potential approach to predict natural variability of communities and thereby improve detection of anthropogenic community change. Using data from minimally disturbed streams, we described natural macrophyte assemblages in pool and riffle habitats separately and in combination, and explored their variation across large scale environmental gradients. Specifically, we developed RIVPACS-type models to predict the presence and abundance of macrophyte taxa at …

0106 biological sciencesbioassessmentRiffleEcologyEcologyNull model010604 marine biology & hydrobiologyagricultural pressureGeneral Decision SciencesSTREAMSpredictive modelsreference condition010603 evolutionary biology01 natural sciencesMacrophyteRIVPACSRIVPACSBorealHabitatwater framework directiveta1181Environmental scienceEcosystemEcology Evolution Behavior and SystematicsEcological Indicators
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Making Every "Point" Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball

2019

Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modelling. The valid and reliable template developed by Francis, Owen and Peters (2019) was used to analyse video footage in S…

Basketballlcsh:BF1-990Applied psychologyLogistic regression050105 experimental psychologyOddsData modelingRC120003 medical and health sciences0302 clinical medicineParalympicPsychology0501 psychology and cognitive sciencesCategorical variableGeneral PsychologyOriginal Researchlogistic regression05 social sciencesOffensiveVDP::Medisinske Fag: 700::Idrettsmedisinske fag: 850sport performance analysisEuropean championshipslcsh:PsychologyElitePsychologypredictive modeling030217 neurology & neurosurgeryPredictive modelling
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Clinical and biochemical determinants of the extent of liver steatosis in type 2 diabetes mellitus

2015

Objective Nonalcoholic fatty liver disease is very frequent in both type 2 diabetes mellitus (T2DM) and the metabolic syndrome (MS), which share clinical and metabolic characteristics. Whether and to which extent these characteristics can predict the degree of liver steatosis are not entirely clear. Patients and methods We determined liver fat (divided into four classes) by standard sonographic images, and clinical and biochemical variables, in 60 consecutive patients with T2DM and with features of the MS. We examined both simple and multiple correlations between the degree of liver steatosis and the variables measured. Results Increased liver fat (defined as >5% of liver mass) was detec…

Malenonalcoholic fatty liver diseasemedicine.medical_specialtytype 2 diabetes mellitusmedicine.medical_treatmentSettore MED/50 - Scienze Tecniche Mediche ApplicateGastroenterologyleptinliver steatosispredictive modelInsulin resistanceNon-alcoholic Fatty Liver DiseaseInternal medicineinsulin resistanceNonalcoholic fatty liver diseasemedicineHumansInsulinAdiposityAgedUltrasonographyvisceral adiposityGlycated HemoglobinMetabolic SyndromeSettore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e FinanziarieModels StatisticalAnthropometryHepatologybusiness.industryInsulinHemoglobin A1c; insulin resistance; leptin; liver steatosis; metabolic control; multiple regression analysis; nonalcoholic fatty liver disease; predictive model; type 2 diabetes mellitus; visceral adiposity;GastroenterologyType 2 Diabetes MellitusHemoglobin A1c; insulin resistance; leptin; liver steatosis; metabolic control; multiple regression analysis; nonalcoholic fatty liver disease; predictive model; type 2 diabetes mellitus; visceral adiposity; Gastroenterology; Hepatologymetabolic controlmultiple regression analysisMiddle AgedHepatologymedicine.diseaseEndocrinologyDiabetes Mellitus Type 2Hemoglobin A1cMetabolic control analysisFemaleWaist CircumferenceSteatosisMetabolic syndromebusinesshemoglobin A1c leptin liver steatosis metabolic control multiple regression analysis nonalcoholic fatty liver disease insulin resistance predictive model type 2 diabetes mellitus visceral adiposity
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