Search results for "predictive model"

showing 10 items of 74 documents

Study of the microstructure and efficiency of YSZ-SPS finely structured ceramic coatings

2018

Thanks to the using of liquid carrier, suspension plasma spray (SPS) enables the manufacture of finely structured coatings. As for conventional plasma spraying (APS), the microstructures of SPS coatings can be tailored by controlling the spray conditions. However, SPS is more complicated than APS due to its number of modifiable parameters.This thesis aims to provide a more fundamental understanding of the relationship between SPS process parameters and the properties of YSZ coatings by identifying generic models based on the use of mathematical statistical methods for the study of influence and sensitivity of the individual parameters.Systematic experiments were carried out to study the inf…

Modèle prédictif[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process EngineeringPredictive modelSuspension plasma sprayProjection plasma de suspensionProcess parameterMultivariate statistics analysisParamètre de procédé[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringPorosityMicrostructurePorositéAnalyse statistique multivariée
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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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Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study

2021

Abstract It is still unclear how genetic information, provided as single‐nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population‐based case‐cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo); selection of the most predictive SNPs among these literature‐co…

Oncologymedicine.medical_specialtyEpidemiologyFramingham Risk Score ; Metabochip ; Coronary Heart Disease ; Genomic Risk Prediction ; Priority-lassoPopulationCoronary DiseaseSingle-nucleotide polymorphismKoronare HerzkrankheitPolymorphism Single NucleotideRisk AssessmentCohort Studies03 medical and health sciencesRisk FactorsInternal medicinemedicineHumansgenomic risk predictionddc:610coronary heart diseaseMetabochipGenetikeducationGenotypingGenetics (clinical)030304 developmental biologypriority‐Lasso0303 health scienceseducation.field_of_studyFramingham Risk ScoreModels GeneticProportional hazards modelbusiness.industry030305 genetics & heredityGenomicsConfidence intervalddc:Coronary disease; GeneticsRisk factorsCohortFramingham risk scorebusinessDDC 610 / Medicine & healthPredictive modelling
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PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches

2019

Geospatial computation, data transformation to a relevant statistical software, and step-wise quantitative performance assessment can be cumbersome, especially when considering that the entire modelling procedure is repeatedly interrupted by several input/output steps, and the self-consistency and self-adaptive response to the modelled data and the features therein are lost while handling the data from different kinds of working environments. To date, an automated and a comprehensive validation system, which includes both the cutoff-dependent and –independent evaluation criteria for spatial modelling approaches, has not yet been developed for GIS based methodologies. This study, for the fir…

Performance analysiEnvironmental EngineeringGeospatial analysis010504 meteorology & atmospheric sciencesComputer scienceSettore GEO/04 - Geografia Fisica E GeomorfologiaComputationGoodness-of-fit010501 environmental sciencescomputer.software_genre01 natural sciencesRobustness (computer science)ValidationEnvironmental ChemistryWaste Management and Disposal0105 earth and related environmental sciencescomputer.programming_languageEnvironmental modellingReceiver operating characteristicSpatial modellingPerformance analysisLandslidePMTPython (programming language)22/4 OA procedurePollutionDrought riskITC-ISI-JOURNAL-ARTICLEData miningPredictive model evaluation frameworkcomputerScience of The Total Environment
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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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Identification of predictive biomarkers for the efficacy of nivolumab in patients with advanced non-small cell cancer.

2019

The recent introduction of immunotherapy has disrupted the management of non-small cell lung cancer (NSCLC). Nivolumab, an antibody targeting the immune checkpoint inhibitor PD-1, has shown remarkable results in seconde-line setting after failure of standard first-line chemotherapy. However, only a quarter of patients benefits from this therapy. To date, no predictive biomarker of the therapeutic efficacy of nivolumab has been identified in a clear and consensual manner. The research for predictive biomarkers of efficacy or resistance to this treatment is, therefore, a major challenge.The emergence of high-throughput sequencing over the past decade has had a significant impact on clinical a…

Predictive modelsBiomarqueursModèles prédictifs[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyLung cancersCancers bronchiquesImmunothérapieNext-Generation sequencingImmunotherapy[SDV.MHEP]Life Sciences [q-bio]/Human health and pathologyBiomarkersSéquençage nouvelle génération
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CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease

2023

AbstractThis study was aimed to investigate the predictive value of the radiomics features extracted from pericoronaric adipose tissue — around the anterior interventricular artery (IVA) — to assess the condition of coronary arteries compared with the use of clinical characteristics alone (i.e., risk factors). Clinical and radiomic data of 118 patients were retrospectively analyzed. In total, 93 radiomics features were extracted for each ROI around the IVA, and 13 clinical features were used to build different machine learning models finalized to predict the impairment (or otherwise) of coronary arteries. Pericoronaric radiomic features improved prediction above the use of risk factors alon…

Predictive modelsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRadiomic featuresCognitive NeuroscienceClinical featuresModel explainabilityComputer Vision and Pattern RecognitionPericoronaric adipose fatCoronary artery diseaseMachine learning classifiersComputer Science ApplicationsCognitive Computation
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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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Forecasts on the development of hydrogen refuelling infrastructures in Portugal

2021

In Portugal, the transition to new forms of mobility has begun in recent years, but there are still obstacles to overcome. Currently, hybrid vehicles (PHEVs) are the most widespread and accepted by the community and that is probably due to range anxiety, having in fact the possibility of double charging (both through the thermal engine and the electric battery). Furthermore, it must be considered that in addition to electric vehicles, another valid alternative to mobility in the near future is the hydrogen vehicles one. These appear to be even more sustainable from the point of view of air emissions, but on the other hand the costs for the production of hydrogen are still too high. Then, th…

Range anxietybusiness.industryMarket trendEnvironmental economicsSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciDiscount pointsHydrogen vehicleMarket researchSettore ING-IND/31 - ElettrotecnicaSmart gridFuel cellsProduction (economics)BusinessElectric mobility Forecasting for FCEV Fuel cell vehicles Hydrogen Plug-in hybrid Predictive model Socio-technical transition
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