Search results for "CROSS-VALIDATION"

showing 10 items of 50 documents

Reliability and validity of the Newcastle Scales in relation to ICD-9-classification

1987

The assessment of endogenous depression by means of the Newcastle Scales (1965, 1971) has been validated by their correlation with biological findings in many previous studies. However, reliability and cross validation studies are lacking for these scales. We found the reliability of the Newcastle Scales to be sufficient or at least moderate in a sample of 70 inpatients with major depression. In order to cross validate both scales, the clinical classification according to ICD-9 and the assessment of the Newcastle Scales have been performed independently in a sample of 112 inpatients with Major Depressive Disorder (RDC). The rate of agreement between clinical diagnosis and classification acc…

AdultMalePsychiatric Status Rating ScalesDepressive Disordermedicine.medical_specialtyPsychometricsPsychometricsTest validityMiddle Agedmedicine.diseaseCross-validationCorrelationPsychiatry and Mental healthRating scaleEndogenous depressionmedicineHumansMajor depressive disorderFemalePsychiatryPsychologyReliability (statistics)Clinical psychologyActa Psychiatrica Scandinavica
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Correlation of Pharmacological Properties of a Group of Hypolipaemic Drugs by Molecular Topology

1996

Abstract This investigation was undertaken to test the ability of the molecular connectivity model to predict the percentage of plasma protein binding, the percentage of total cholesterol reduction and oral LD50 in rats of a group of hypolipaemic drugs using multi-variable regression equations with multiple correlation coefficients, standard error of estimate, degrees of freedom, F-Snedecor function values, Mallow's CP and Student's t-test as criteria of fit. Regression analyses showed that the molecular connectivity model predicts these properties. Corresponding stability (cross validation) studies were made on the selected prediction models which confirmed their goodness of fit. The resul…

Molecular modelStereochemistryDegrees of freedom (statistics)Pharmaceutical ScienceModels BiologicalCross-validationLethal Dose 50CorrelationStructure-Activity RelationshipFenofibrateGoodness of fitAnimalsMultiple correlationFuransHypolipidemic AgentsPharmacologyChemistryBlood ProteinsRegressionRatsCholesterolProbucolStandard errorRegression AnalysisBiological systemProtein BindingJournal of Pharmacy and Pharmacology
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<strong>Predicting Proteasome Inhibition using Atomic Weighted Vector and Machine Learning</strong>

2018

Ubiquitin/Proteasome System (UPS) is a highly regulated mechanism of intracellular protein degradation and turnover. Through the concerted actions of a series of enzymes, proteins are marked for proteasomal degradation by being linked to the polypeptide co-factor, ubiquitin. The UPS participates in a wide array of biological functions such as antigen presentation, regulation of gene transcription and the cell cycle, and activation of NF-κB. Some researchers have applied QSAR method and machine learning in the study of proteasome inhibition (EC50(µmol/L)), such as: the analysis of proteasome inhibition prediction, in the prediction of multi-target inhibitors of UPP and in the prediction of p…

Quantitative structure–activity relationshipbusiness.industryProtein contact mapPerceptronMachine learningcomputer.software_genreCross-validationRandom forestStatistical classificationMolecular descriptorLinear regressionArtificial intelligencebusinesscomputerMathematicsProceedings of MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition
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Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs

2006

Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear in…

Quantitative structure–activity relationshipDatabases FactualMolecular modelStereochemistryClinical BiochemistryDrug Evaluation PreclinicalPharmaceutical ScienceAntitrichomonal AgentsLigandsBiochemistryCross-validationChemometricsStructure-Activity Relationshipchemistry.chemical_compoundArtificial IntelligencePredictive Value of TestsMolecular descriptorDrug DiscoveryTrichomonas vaginalisAnimalsCluster AnalysisComputer SimulationMolecular BiologyStochastic ProcessesOrganic ChemistryComputational BiologyReproducibility of ResultsLinear discriminant analysisAntitrichomonal agentchemistryData Interpretation StatisticalTopological indexLinear ModelsMolecular MedicineBiological systemAlgorithmsBioorganic & Medicinal Chemistry
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Cross validation of the 1-mile walking test for men with mental retardation.

1997

The purpose of this study was to cross validate the equation developed by Rintala et al. (1992) to estimate the cardiorespiratory efficiency of men with mental retardation (MR). Subjects were 19 healthy men (27 ± 8 yr) with MR (IQ = 58 ± 12). Following familiarization, a graded maximal treadmill test and two 1-mile walk tests (Rockport Fitness Walking Test, RFWT) were administered. The peak VO 2 value was the criterion measure used to cross validate the equation. The equation was: Peak VO 2 (ml.kg -1 .min -1 ) = 101.92 - 2.356 (MILE) -0.420 (WEIGHT). The mean differences were 2.04 (MILE 1 )(P = 0.02) and 2.43 (MILE 2 )(P = 0.004) ml.kg -1 .min -1 . A significant positive correlation was fou…

AdultMalePopulationPhysical fitnessPhysical Therapy Sports Therapy and RehabilitationWalkingCross-validationCardiovascular Physiological PhenomenaOxygen ConsumptionIntellectual DisabilityStatisticsHumansOrthopedics and Sports MedicineTreadmilleducationMathematicsMileeducation.field_of_studyWalking testbusiness.industryRespirationReproducibility of ResultsCardiorespiratory fitnessStandard errorPhysical FitnessExercise TestbusinessMedicine and science in sports and exercise
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Confidence bands for Horvitz-Thompson estimators using sampled noisy functional data

2013

When collections of functional data are too large to be exhaustively observed, survey sampling techniques provide an effective way to estimate global quantities such as the population mean function. Assuming functional data are collected from a finite population according to a probabilistic sampling scheme, with the measurements being discrete in time and noisy, we propose to first smooth the sampled trajectories with local polynomials and then estimate the mean function with a Horvitz-Thompson estimator. Under mild conditions on the population size, observation times, regularity of the trajectories, sampling scheme, and smoothing bandwidth, we prove a Central Limit theorem in the space of …

Statistics and ProbabilityFOS: Computer and information sciencesmaximal inequalitiesCovariance functionCLTPopulationSurvey samplingweighted cross-validationMathematics - Statistics TheoryStatistics Theory (math.ST)Methodology (stat.ME)symbols.namesakeFOS: Mathematicssurvey samplingeducationGaussian processfunctional dataStatistics - Methodologysuprema of Gaussian processesMathematicsCentral limit theoremeducation.field_of_studySampling (statistics)Estimatorspace of continuous functionssymbolslocal polynomial smoothingAlgorithmSmoothing
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A General Frame for Building Optimal Multiple SVM Kernels

2012

The aim of this paper is to define a general frame for building optimal multiple SVM kernels. Our scheme follows 5 steps: formal representation of the multiple kernels, structural representation, choice of genetic algorithm, SVM algorithm, and model evaluation. The computation of the optimal parameter values of SVM kernels is performed using an evolutionary method based on the SVM algorithm for evaluation of the quality of chromosomes. After the multiple kernel is found by the genetic algorithm we apply cross validation method for estimating the performance of our predictive model. We implemented and compared many hybrid methods derived from this scheme. Improved co-mutation operators are u…

Scheme (programming language)Multiple kernel learningbusiness.industryComputationPattern recognitionCross-validationSupport vector machineGenetic algorithmArtificial intelligenceGeneral framebusinesscomputerKernel (category theory)Mathematicscomputer.programming_language
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Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series

2006

A method to evaluate the direction and strength of causal interactions in bivariate cardiovascular and cardiorespiratory series is presented. The method is based on quantifying self and mixed predictability of the two series using nearest-neighbour local linear approximation. It returns two causal coupling indexes measuring the relative improvement in predictability along direct and reverse directions, and a directionality index indicating the preferential direction of interaction. The method was implemented through a cross-validation approach that allowed quantification of directionality without constraining the embedding of the series, and fully exploited the available data to maximise th…

AdultStatistics as TopicBiomedical EngineeringInferenceBlood PressureHealth InformaticsBivariate analysisDirectionalityCross-validationGranger causalityHeart RateStatisticsEconometricsHumansComputer SimulationPredictabilityMathematicsSeries (mathematics)Models CardiovascularNonlinear systemNonlinear DynamicsData Interpretation StatisticalShort-term cardiovascular variabilityRespiratory MechanicsRegression AnalysisFemaleNon-linear predictionLinear approximationAlgorithmsBiomedizinische Technik/Biomedical Engineering
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Model performance of partial least squares in utilizing the visible spectroscopy data for estimation of algal biomass in a photobioreactor

2018

[EN] Spectroscopy technology and statistical methods (Partial Least Squares) have been integrated to develop a model that allows estimating the microalgal biomass in a photobioreactor. The model employing PLS combines the absorption spectrum measurements in the visible range (400-750 nm) with a microalgae cell density in a water sample. First, a calibration model was constructed using a calibration data set, and then, the predictive capacity of the model was determined by cross validation. Finally, an external validation of the predictive performance of the model was carried out with an independent data set. To test the accuracy of the model it was applied to different culture conditions yi…

Microalgae biomass010504 meteorology & atmospheric sciencesAbsorption spectraSoil SciencePhotobioreactorPhotobioreactorPlant Science010501 environmental sciences01 natural sciencesPartial Least SquaresCross-validationSet (abstract data type)Data setUltraviolet visible spectroscopyPartial least squares regressionCalibrationSpectroscopyBiological systemScenedesmus spTECNOLOGIA DEL MEDIO AMBIENTE0105 earth and related environmental sciencesGeneral Environmental ScienceMathematics
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Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

2021

Abstract Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-valida…

Lung NeoplasmsComputer scienceBiophysicsGeneral Physics and AstronomySample (statistics)Cross validationMachine learningcomputer.software_genreCross validation; Machine learning; Non-small cell lung cancer; Radiomics; Humans; Lung; Machine Learning; Neoplasm Staging; Carcinoma Non-Small-Cell Lung; Lung NeoplasmsCross-validationSet (abstract data type)Machine LearningNon-small cell lung cancerCarcinoma Non-Small-Cell LungmedicineHumansRadiology Nuclear Medicine and imagingStage (cooking)Lung cancerNon-Small-Cell LungLungNeoplasm StagingSmall dataRadiomicsbusiness.industryCarcinomaGeneral Medicinemedicine.diseaseRandom forestSupport vector machineArtificial intelligencebusinesscomputer
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