Search results for "Linear Discriminant Analysi"

showing 10 items of 164 documents

Burned bones forensic investigations employing near infrared spectroscopy

2017

The use of near infrared (NIR) spectroscopy was evaluated, by using chemometric tools, for the study of the environmental impact on burned bones. Spectra of internal and external parts of burned bones, together with sediment samples, were treated by Principal Component Analysis and cluster classification as exploratory techniques to select burned bone samples, less affected by environmental processes, to properly carry out forensic studies. Partial Least Square Discriminant Analysis was used to build a model to classify bone samples based on their burning conditions, providing an efficient and accurate method to discern calcined and carbonized bone. Additionally, Partial Least Square regres…

010506 paleontologyStrontiumMaterials scienceMagnesium010401 analytical chemistryNear-infrared spectroscopychemistry.chemical_elementMineralogyLinear discriminant analysis01 natural sciences0104 chemical scienceschemistryPrincipal component analysisPartial least squares regressionNir spectra1607SpectroscopySpectroscopy0105 earth and related environmental sciencesVibrational Spectroscopy
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Use of Leaf and Fruit Morphometric Analysis to Identify and Classify White Mulberry (Morus alba L.) Genotypes

2018

Digital image analysis and multivariate data analysis were used in this study to identify a set of leaf and fruit morphometric traits to discriminate white mulberry (Morus alba L.) cultivars. The trial was conducted using three- to five-year-old potted cuttings of several white mulberry cultivars. 32 leaf morphometric descriptors were recorded in 2011 and 2012 from 11 mulberry cultivars using image analysis of scanned leaves, whereas six fruit descriptors were recorded in 2011 from nine mulberry cultivars. Linear discriminant analysis (LDA) was used to identify a subset of measured variables that could discriminate the cultivars in trial. Biplot analysis, followed by cluster analysis, was p…

0106 biological sciencesLinear discriminant analysifood.ingredientlinear discriminant analysisBiplotPlant ScienceBiology01 natural sciencesCutting0404 agricultural biotechnologyfoodGenotypedescriptordigital image analysisLeaf sizeCultivarlcsh:Agriculture (General)MorphometricsMultivariate analysi<i>Morus alba</i>Digital image analysi04 agricultural and veterinary sciencesLinear discriminant analysislcsh:S1-972040401 food scienceMorus albaHorticulturemultivariate analysisWhite MulberryAgronomy and Crop Sciencebiplot010606 plant biology & botanyFood ScienceAgriculture
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Dry selection and wet evaluation for the rational discovery of new anthelmintics

2017

Helminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmin…

0301 basic medicineBiophysicsNon-stochastic and stochastic atom-based bilinear indicesBilinear interpolationLDA-based QSAR modelQuBiLs-MAS module01 natural sciencesSet (abstract data type)03 medical and health sciencesMolecular descriptorStatisticsPhysical and Theoretical ChemistryMolecular BiologySelection (genetic algorithm)MathematicsFree and open source softwareTraining setTOMOCOMD-CARDD softwareExternal validationAnthelmintic activityAtom (order theory)Computational creeningCondensed Matter PhysicsLinear discriminant analysis0104 chemical sciencesIndazole010404 medicinal & biomolecular chemistry030104 developmental biologyLead generationMolecular Physics
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Mass Spectrometry Imaging Differentiates Chromophobe Renal Cell Carcinoma and Renal Oncocytoma with High Accuracy

2020

Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin…

0301 basic medicineChromophobe Renal Cell Carcinoma610610 Medicine & healthmass spectrometry imagingBiologyCross-validationMass spectrometry imagingOncocytic renal tumors03 medical and health sciences0302 clinical medicineproteomics10049 Institute of Pathology and Molecular PathologymedicineRenal oncocytomachromophobe renal cell carcinomabusiness.industrymedicine.diseaseLinear discriminant analysisRandom forestSupport vector machine030104 developmental biologyOncology030220 oncology & carcinogenesis2730 OncologyDifferential diagnosisNuclear medicinebusinessrenal oncocytomaResearch PaperJournal of Cancer
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2020

Background Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects. Results We systematically evaluated the performance of univariate ANOVA, Welch’s ANOVA and linear mixed effects models …

0301 basic medicineMultivariate statisticsMultidisciplinaryUnivariateContrast (statistics)Linear discriminant analysis03 medical and health sciences030104 developmental biology0302 clinical medicineMultivariate analysis of variancePrincipal component analysisPartial least squares regressionStatisticsAnalysis of variance030217 neurology & neurosurgeryMathematicsPLOS ONE
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Search of Chemical Scaffolds for Novel Antituberculosis Agents

2005

3 A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three tech- niques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear re- gression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N…

0301 basic medicineStereochemistryAntitubercular AgentsQuantitative Structure-Activity RelationshipComputational biology01 natural sciencesBiochemistryAnalytical ChemistryMycobacterium tuberculosis03 medical and health sciencesmedicineComputer SimulationMycobacterium avium complexEthambutolVirtual screeningMolecular StructurebiologyChemistrybiology.organism_classificationLinear discriminant analysis0104 chemical sciences010404 medicinal & biomolecular chemistry030104 developmental biologyModels ChemicalDrug DesignRegression AnalysisMolecular MedicineMultiple linear regression analysisBiotechnologyPentamidinemedicine.drugSLAS Discovery
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Scenario-based discrimination of common grapevine varieties using in-field hyperspectral data in the western of Iran

2019

Abstract Field spectroscopy is an accurate, rapid and nondestructive technique for monitoring of agricultural plant characteristics. Among these, identification of grapevine varieties is one of the most important factors in viticulture and wine industry. This study evaluated the discriminatory ability of field hyperspectral data and statistical techniques in case of five common grapevine varieties in the western of Iran. A total of 3000 spectral samples were acquired at leaf and canopy levels. Then, in order to identify the best approach, two types of hyperspectral data (wavelengths from 350 to 2500 nm and 32 spectral indices), two data reduction methods (PLSR and ANOVA-PCA) and two classif…

2. Zero hungerCanopyGlobal and Planetary ChangeScenario based010504 meteorology & atmospheric sciences0211 other engineering and technologiesRed edgeHyperspectral imaging02 engineering and technology15. Life on landManagement Monitoring Policy and LawLinear discriminant analysis01 natural sciencesArticleField (geography)StatisticsComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesData reductionWine industryMathematicsInternational Journal of Applied Earth Observation and Geoinformation
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Estimation of ADME Properties in Drug Discovery: Predicting Caco-2 Cell Permeability Using Atom-Based Stochastic and Non-stochastic Linear Indices

2007

The in vitro determination of the permeability through cultured Caco-2 cells is the most often-used in vitro model for drug absorption. In this report, we use the largest data set of measured P(Caco-2), consisting of 157 structurally diverse compounds. Linear discriminant analysis (LDA) was used to obtain quantitative models that discriminate higher absorption compounds from those with moderate-poorer absorption. The best LDA model has an accuracy of 90.58% and 84.21% for training and test set. The percentage of good correlation, in the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA), was greater than 81%. In addition, multiple …

Absorption (pharmacology)Stochastic ProcessesVirtual screeningQuantitative structure–activity relationshipDrug discoveryStereochemistryLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisPermeabilityData setROC CurveDrug DesignTest setLinear regressionLinear ModelsHumansPharmacokineticsCaco-2 CellsBiological systemADMEMathematicsJournal of Pharmaceutical Sciences
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Four Wellbeing Patterns and their Antecedents in Millennials at Work

2018

Literature suggests that job satisfaction and health are related to each other in a synergic way. However, this might not always be the case, and they may present misaligned relationships. Considering job satisfaction and mental health as indicators of wellbeing at work, we aim to identify four patterns (i.e., satisfied-healthy, unsatisfied-unhealthy, satisfied-unhealthy, and unsatisfied-healthy) and some of their antecedents. In a sample of 783 young Spanish employees, a two-step cluster analysis procedure showed that the unsatisfied-unhealthy pattern was the most frequent (33%), followed by unsatisfied-healthy (26.6%), satisfied-unhealthy (24.8%) and, finally, the satisfied-healthy patter…

AdultMaleAdolescentHealth Toxicology and Mutagenesismedia_common.quotation_subjectHealth Statuslcsh:Medicine050109 social psychologySample (statistics)WorkloadDisease clusterRole conflictArticleYoung Adultwellbeing0502 economics and businessHumans0501 psychology and cognitive sciencesMillennialsmedia_commonjob satisfactionwellbeing misalignment05 social scienceslcsh:RPublic Health Environmental and Occupational HealthOverqualificationhealthAmbiguityLinear discriminant analysisMental healthMental HealthSpainJob satisfactionFemalePsychologySocial psychology050203 business & managementInternational Journal of Environmental Research and Public Health
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Sensing gastric cancer via point‐of‐care sensor breath analyzer

2021

Background Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. Methods A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant an…

AdultMaleCancer ResearchValidation studymedicine.medical_specialtyvolatile organic compoundPoint-of-Care SystemsBiosensing TechniquesSensitivity and Specificity03 medical and health sciences0302 clinical medicineSDG 3 - Good Health and Well-beingbreath analyzerStomach NeoplasmsCancer screeningmedicineHumansNanotechnology030212 general & internal medicinePoint of careAgedAged 80 and overbusiness.industrygastric cancerscreeningCancerpersonalizedDiscriminant AnalysisGastric lesionsMiddle Agedmedicine.diseaseLinear discriminant analysisprecancerous lesion3. Good healthBreath analyzerOncologyBreath Tests030220 oncology & carcinogenesisArea Under CurveCase-Control Studies/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingFemaleRadiologyInternet of ThingsbusinessPrecancerous ConditionsCancer
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