Search results for "Predictive modelling"

showing 10 items of 35 documents

A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Popu…

2021

Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models wer…

PopulationMachine learningcomputer.software_genreLogistic regressionPediatricsProcalcitoninRJ1-570Medicinerisk factorseducationOriginal Researcheducation.field_of_studyKawasaki diseasebusiness.industryRetrospective cohort studyNomogrammedicine.diseaseSupport vector machineprediction modelmachine learningPediatrics Perinatology and Child HealthKawasaki diseaseArtificial intelligencebusinesscomputerintravenous immunoglobulin resistancePredictive modellingFrontiers in Pediatrics
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Validation and update of the thoracic surgery scoring system (Thoracoscore) risk model.

2020

Abstract OBJECTIVES The performance of prediction models tends to deteriorate over time. The purpose of this study was to update the Thoracoscore risk prediction model with recent data from the Epithor nationwide thoracic surgery database. METHODS From January 2016 to December 2017, a total of 56 279 patients were operated on for mediastinal, pleural, chest wall or lung disease. We used 3 recommended methods to update the Thoracoscore prediction model and then proceeded to develop a new risk model. Thirty-day hospital mortality included patients who died within the first 30 days of the operation and those who died later during the same hospital stay. RESULTS We compared the baseline patient…

Pulmonary and Respiratory MedicineLung Diseasesmedicine.medical_specialtyCalibration (statistics)030204 cardiovascular system & hematologyOverfittingRisk Assessment03 medical and health sciencesRisk model0302 clinical medicineGoodness of fitRisk FactorsmedicineThoracoscopyHumansHospital MortalityAgedPerformance statusmedicine.diagnostic_testbusiness.industryThoracic SurgeryGeneral MedicineThoracic Surgical Procedures030228 respiratory systemROC CurveCardiothoracic surgeryEmergency medicineSurgeryCardiology and Cardiovascular MedicinebusinessPredictive modellingEuropean journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
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QSAR Analysis of Hypoglycemic Agents Using the Topological Indices

2001

The molecular topology model and discriminant analysis have been applied to the prediction of some pharmacological properties of hypoglycemic drugs using multiple regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies performed on the selected prediction models confirmed the goodness of the fits. The method used for hypoglycemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new hypoglycemic agents, and we …

Quantitative structure–activity relationshipbusiness.industryStatistical parameterRegression analysisPattern recognitionGeneral ChemistryMachine learningcomputer.software_genreLinear discriminant analysisStability (probability)Computer Science ApplicationsComputational Theory and MathematicsLinear regressionArtificial intelligencebusinesscomputerPredictive modellingSelection (genetic algorithm)Information SystemsMathematics
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Soil erosion modelling: a global review and statistical analysis

2021

40 Pags.- 10 Figs.- 2 Tabls.- Suppl. Informat. The definitive version is available at: https://www.sciencedirect.com/science/journal/00489697

Research literatureEnvironmental EngineeringErosion rates010504 meteorology & atmospheric sciencesComputer scienceGeography & travelReview[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study010501 environmental sciencesErosion rate01 natural sciencesPolicy supportModellingITC-HYBRIDErosion rates; GIS; Land degradation; Land sustainability; Modelling; Policy supportddc:550Environmental ChemistryLand sustainabilityStatistical analysisWaste Management and Disposal0105 earth and related environmental sciencesddc:910WIMEKbusiness.industryEnvironmental resource managementCollective intelligenceBodemfysica en Landbeheer15. Life on landPE&RCGISPollutionSoil Physics and Land ManagementITC-ISI-JOURNAL-ARTICLESustainabilityErosionLand degradationLand degradationbusinessISRIC - World Soil InformationPredictive modelling
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A Comprehensive Check of Usle-Based Soil Loss Prediction Models at the Sparacia (South Italy) Site

2020

At first, in this paper a general definition of the event rainfall-runoff erosivity factor for the USLE-based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single-storm erosion index and b1 and b2 are coefficients, was introduced. The rainfall-runoff erosivity factors of the USLE (b1 = 0, b2 = 1), USLE-M (b1 = b2 = 1), USLE-MB (b1 ≠ 1, b2 = 1), USLE-MR (b1 = 1, b2 ≠ 1), USLE-MM (b1 = b2 ≠ 1) and USLE-M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then, the different expressions of REFe were simultaneously tested against a dataset of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predict…

Runoff coefficientUSLE-type erosion modelsSoil lossSoil loss predictionStatisticsExponentEvent soil loSoil erosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliPredictive modellingPlot (graphics)MathematicsEvent (probability theory)
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Geospatial modelling and map analysis allowed measuring regression of the upper limit of Posidonia oceanica seagrass meadows under human pressure

2018

Abstract Marine coastal ecosystems are facing structural and functional changes due to the increasing human footprint worldwide, and the assessment of their long-term changes becomes particularly challenging. Measures of change can be done by comparing the observed ecosystem status to a purposely defined reference condition. In this paper, a geospatial modelling approach based on 2D mapping and morphodynamic data was used to predict the natural position of the upper limit (i.e., the landward continuous front) of Posidonia oceanica seagrass meadows settled on soft bottom. This predictive model, formerly developed at the regional spatial scale, was here applied for the first time at the Medit…

Settore BIO/07 - Ecologia0106 biological sciencesMediterranean climateGeospatial analysis010504 meteorology & atmospheric sciencesMediterranean sea Morphodynamic sPosidonia oceanica Predictive modelling Reference conditions SeagrassAquatic ScienceOceanographycomputer.software_genre01 natural sciencesMorphodynamicZoologíaEcosystemSeagrasssPosidonia oceanica0105 earth and related environmental sciencesbiology010604 marine biology & hydrobiologySeagraPredictive modellingFragmentation (computing)Posidonia oceanicaReference conditionsbiology.organism_classificationSeagrass;Predictive modelling;Reference conditions;Morphodynamics;Posidonia oceanica;Mediterranean seaMorphodynamicsRegressionSeagrassPosidonia oceanicaSettore BIO/03 - Botanica Ambientale E ApplicataMediterranean seaSpatial ecologyEnvironmental scienceReference conditionPhysical geographycomputerEstuarine, Coastal and Shelf Science
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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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Importance of the Window Function Choice for the Predictive Modelling of Memristors

2021

Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absenc…

State variableComputer science02 engineering and technologyMemristorType (model theory)Fixed pointTopologyWindow functionlaw.inventionPredictive modelsComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologiesMathematical modellawAttractor0202 electrical engineering electronic engineering information engineeringEvolution (biology)Electrical and Electronic EngineeringPolarity (mutual inductance)threshold voltage020208 electrical & electronic engineeringmemristive systemsBiological system modeling020206 networking & telecommunicationsWindow functionmemristorsIntegrated circuit modelingPredictive modellingIEEE Transactions on Circuits and Systems Ii-Express Briefs
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Practical thresholds to distinguish erosive and rill rainfall events

2019

Abstract In this paper, 1017 rainfall events from 2008 to 2017 are used to identify the rainfall threshold that produces upland erosion at the Masse (central Italy) and Sparacia (southern Italy) experimental stations. The rainfall events are classified into three classes: non-erosive, interrill-only and rill. The threshold values for separating as correctly as possible the erosive rains (case I) and the rill rains (case II) are derived solely from the hyetograph. Each threshold value is obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events (case I) or only rill events (case II). The performances of selec…

Water erosionThreshold limit valueRainfall patternSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliRUSLEUSLETruncation (statistics)Interrill; Rainfall erosivity; Rainfall hyetograph; Rainfall pattern; Rainfall thresholds; RUSLE; Soil erosion; Soil loss; USLERainfall hyetographWater Science and TechnologyHydrologySoil logeographyRainfall thresholdsgeography.geographical_feature_categoryInterrillRainfall erosivityRainfall thresholdSoil lossRillHyetographSoil erosionErosionEnvironmental scienceScale (map)Predictive modellingJournal of Hydrology
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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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