Search results for "datasets"

showing 10 items of 45 documents

Use of the KSVM-based system for the definition, validation and identification of the incisional hernia recurrence risk factors

2019

BACKGROUND: Incisional hernia is one of the most common complications after abdominal surgery with an incidence rate of 11 to 20% post laparotomy. Many different factors can be considered as risk factors of incisional hernia recurrence. The aim of this study is to confirm and to validate the incisional hernia recurrence risk factors and to identify and to validate new ones. METHODS: In the period from July 2007 to July 2017, 154 patients were selected and subjected to incisional hernia repair. The surgical operations were conducted under general anaesthesia. Patients received antibiotic prophylaxis when indicated, according to the hospital prophylaxis scheme. Inclusion criteria of the study…

Data AnalysisMaleAge FactorsDatasets as TopicIncisional hernia - Risk factors - Recurrence - KSVM.ComorbidityAnesthesia GeneralAntibiotic ProphylaxisMiddle AgedSensitivity and SpecificityBody Mass IndexMachine LearningSex Factorssurgical procedures operativeRecurrenceRisk Factorsincisional hernia risk factorsData MiningHumansIncisional HerniaFemale
researchProduct

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

2021

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ec…

Data DescriptorDistribuição GeográficaPlan_S-Compliant-OASoilBiomassbiodiversityDiversityEcologyBiodiversidadeQBiodiversityeliöyhteisötmaaperäeliöstöPE&RCComputer Science ApplicationsMultidisciplinary SciencesBiogeographyinternational1181 Ecology evolutionary biologyEcosystem engineersScience & Technology - Other TopicsStatistics Probability and UncertaintyInformation SystemsStatistics and ProbabilitylierotScienceInvertebradosLibrary and Information Sciences[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyEcology and EnvironmentEducationeliömaantiede[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsMinhocaServiço ambientalBIODIVERSITY CHANGELife ScienceEcosystem servicesEarthwormsDatasetsAnimalsSpatial distributionCommunity ecologyOligochaetaLaboratorium voor NematologieEcosystem1172 Environmental sciencesbiogeographyScience & TechnologyLAND-USEBiology and Life SciencesPLATFORMBodemfysica en LandbeheerEcologíaEcossistemabiodiversiteettiSoil Physics and Land ManagementSoloBiologia do Solomaaperäeläimistö570 Life sciences; biologyeartworm ; abundance ; biomass ; diversityLaboratory of Nematology[SDE.BE]Environmental Sciences/Biodiversity and EcologyCOMMUNITIEScommunity ecology
researchProduct

Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex

2019

14 páginas, 6 figuras

Datasets as TopicGene ExpressionBacterial lineagesPopulation genomicsNegative selectionMUTATIONPathogenSensor kinaseResearch ArticlesHistory AncientPhylogenyRecombination Genetic0303 health sciencesMultidisciplinaryHYPOTHESIS1184 Genetics developmental biology physiologySciAdv r-articlesLINEAGE3. Good healthPast and presentPositive selectionMycobacterium tuberculosis complexHost-Pathogen InteractionsTwo component systemsResearch ArticleLineage (genetic)Genetic SpeciationVirulence FactorsVirulenceBiologyMicrobiologyHistory 21st CenturyRecombination eventsMycobacterium03 medical and health sciencesBacterial ProteinsGenetic algorithmGeneticsHumansTuberculosisSelection GeneticGene030304 developmental biologyGenetic locus030306 microbiologyMycobacterium tuberculosis complexesMycobacterium tuberculosisbiology.organism_classificationEVOLUTIONGenetic SpeciationGenetic LociEvolutionary biologyVIRULENCEAdaptationGenome BacterialRESISTANCE
researchProduct

Human experts vs. machines in taxa recognition

2020

The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards the ability and logic of machines. In our study, we investigate both the differences in accuracy and in the identification logic of taxonomic experts and machines. We propose a systematic approach utilizing deep Convolutional Neural Nets with the transfer learning paradigm and extensively evaluate it over a multi-pose taxonomic dataset with hierarchical labels specifically created for this comparison. We also study the prediction accuracy on different ranks of taxonomic hier…

FOS: Computer and information sciencesComputer Science - Machine Learninghahmontunnistus (tietotekniikka)Computer scienceClassification approachTaxonomic expert02 engineering and technologyneuroverkotcomputer.software_genreConvolutional neural networkQuantitative Biology - Quantitative MethodsField (computer science)Machine Learning (cs.LG)Machine learning approachesStatistics - Machine LearningAutomated approachDeep neural networks0202 electrical engineering electronic engineering information engineeringTaxonomic rankQuantitative Methods (q-bio.QM)Classification (of information)Artificial neural networksystematiikka (biologia)Prediction accuracyIdentification (information)koneoppiminenMulti-image dataBenchmark (computing)020201 artificial intelligence & image processingConvolutional neural networksComputer Vision and Pattern RecognitionClassification errorsMachine Learning (stat.ML)Machine learningState of the artElectrical and Electronic EngineeringTaxonomySupport vector machinesLearning systemsbusiness.industryNode (networking)020206 networking & telecommunicationsComputer circuitsHierarchical classificationConvolutionSupport vector machineFOS: Biological sciencesTaxonomic hierarchySignal ProcessingBiomonitoringBenchmark datasetsArtificial intelligencebusinesscomputertaksonitSoftware
researchProduct

Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm

2016

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…

FOS: Computer and information sciencesreduced computationGaussianModels NeurologicalDatasets as Topicta3112Statistics - ComputationStatistics - ApplicationsTime030218 nuclear medicine & medical imagingMethodology (stat.ME)Diffusion03 medical and health sciencessymbols.namesake0302 clinical medicineScoring algorithmRician fadingPrior probabilityExpectation–maximization algorithmImage Processing Computer-AssistedMaximum a posteriori estimationHumansApplications (stat.AP)Computer SimulationComputation (stat.CO)Statistics - MethodologyMathematicsta112Likelihood FunctionsGeneral NeuroscienceBrainEstimatormaximum likelihood estimatorFisher scoringMagnetic Resonance ImagingWhite MatterRician likelihoodDiffusion Tensor ImagingFourier transformNonlinear Dynamicssymbolsmaximum a posteriori estimatorAlgorithmAlgorithms030217 neurology & neurosurgerydata augmentation
researchProduct

Ancestry and demography and descendants of Iron Age nomads of the Eurasian Steppe

2017

During the 1st millennium before the Common Era (BCE), nomadic tribes associated with the Iron Age Scythian culture spread over the Eurasian Steppe, covering a territory of more than 3,500 km in breadth. To understand the demographic processes behind the spread of the Scythian culture, we analysed genomic data from eight individuals and a mitochondrial dataset of 96 individuals originating in eastern and western parts of the Eurasian Steppe. Genomic inference reveals that Scythians in the east and the west of the steppe zone can best be described as a mixture of Yamnaya-related ancestry and an East Asian component. Demographic modelling suggests independent origins for eastern and western g…

Gene FlowMale0301 basic medicineSteppePopulation geneticsHuman MigrationGenomic dataBiological anthropologyScience[SHS.ANTHRO-BIO]Humanities and Social Sciences/Biological anthropologyDatasets as TopicGeneral Physics and AstronomyDNA MitochondrialWhite PeopleArticleGeneral Biochemistry Genetics and Molecular BiologyRussia03 medical and health sciencesAsian Peopleddc:590HumansEast AsiaHistory AncientTransients and MigrantsModels StatisticalMultidisciplinarygeography.geographical_feature_categoryHuman migrationbusiness.industryQGenetic VariationGeneral ChemistryGrasslandKazakhstan030104 developmental biologyGeographyIron AgeEthnologybusiness
researchProduct

Characterization of a fractured basement reservoir using high-resolution 3D seismic and logging datasets: A case study of the Sab'atayn Basin, Yemen.

2018

The Sab'atayn Basin is one of the most prolific Mesozoic hydrocarbon basins located in central Yemen. It has many oil producing fields including the Habban Field with oil occurrences in fractured basement rocks. A comprehensive seismic analysis of fractured basement reservoirs was performed to identify the structural pattern and mechanism of hydrocarbon entrapment and reservoir characteristics. A 3D post-stack time migration seismic cube and logging data of 20 wells were used and several 2D seismic sections were constructed and interpreted. Depth structure maps were generated for the basement reservoir and overlying formations. The top of the basement reservoir is dissected by a set of NW-S…

Geologic SedimentsYemen010504 meteorology & atmospheric sciencesOutcropWater WellsDatasets as TopicGeographic Mappinglcsh:Medicine010502 geochemistry & geophysicsBiochemistry01 natural scienceschemistry.chemical_compoundJurassic PeriodOil and Gas FieldsPetrologylcsh:ScienceMaterialsSeismologyMineralsCretaceous PeriodMultidisciplinaryHydraulic FrackingPhysicsClassical MechanicsGeologyMineralogyLipidsPetroleum reservoirChemistryGeophysicsPetroleumBasement (geology)Source rockPhysical SciencesMesozoic EraPetroleumOrganic MaterialsPorosityGeologyResearch ArticleMaterials ScienceGraniteNatural GasStructural basinImaging Three-DimensionalEarthquakesHumans0105 earth and related environmental sciencesDamage Mechanicslcsh:RChemical CompoundsBiology and Life SciencesDrillingGeologic TimeHydrocarbonschemistryEarth SciencesGeographic Information Systemslcsh:QOilsOil shalePLoS ONE
researchProduct

Big Data in Medical Science–a Biostatistical View

2015

Big data” is a universal buzzword in business and science, referring to the retrieval and handling of ever-growing amounts of information. It can be assumed, for example, that a typical hospital generates hundreds of terabytes (1 TB = 1012 bytes) of data annually in the course of patient care (1). For instance, exome sequencing, which results in 5 gigabytes (1 GB = 109 bytes) of data per patient, is on the way to becoming routine (2). The analysis of such enormous volumes of information, i.e., organization and description of the data and the drawing of (scientifically valid) conclusions, can already hardly be accomplished with the traditional tools of computer science and statistics. For ex…

Gigabytebusiness.industrymedia_common.quotation_subjectBig dataByteCloud computingGeneral MedicineTerabyteBioinformaticsData scienceData analysisMedicinebusinessFunction (engineering)media_commonDatasets as TopicDeutsches Ärzteblatt international
researchProduct

Pathological significance and prognostic value of surfactant protein D in cancer

2018

Surfactant protein D (SP-D) is a pattern recognition molecule belonging to the Collectin (collagen-containing C-type lectin) family that has pulmonary as well as extra-pulmonary existence. In the lungs, it is a well-established opsonin that can agglutinate a range of microbes, and enhance their clearance via phagocytosis and super-oxidative burst. It can interfere with allergen–IgE interaction and suppress basophil and mast cell activation. However, it is now becoming evident that SP-D is likely to be an innate immune surveillance molecule against tumor development. SP-D has been shown to induce apoptosis in sensitized eosinophils derived from allergic patients and a leukemic cell line via …

Male0301 basic medicineLung NeoplasmsDatasets as Topic0302 clinical medicineEpidermal growth factorNeoplasmsImmunology and AllergyRNA NeoplasmOriginal ResearchCancerOvarian NeoplasmsInnate immunitySurfactant protein DBioinformatics analysiPrognosisPulmonary Surfactant-Associated Protein DImmunohistochemistryTumor microenvironment030220 oncology & carcinogenesisAdenocarcinomaFemaleCancersBreast NeoplasmHumanlcsh:Immunologic diseases. AllergyPrognosiImmunologyBreast NeoplasmsBiology03 medical and health sciencesImmune systemBioinformatics analysisStomach NeoplasmsStomach NeoplasmBiomarkers TumormedicineHumansComputer SimulationLung cancerTumor microenvironmentOvarian NeoplasmComputational BiologySurfactant protein DCancermedicine.diseaseSurvival AnalysisLung NeoplasmImmune surveillance030104 developmental biologyCancer researchNeoplasmBioinformatics analysis; Cancers; Immune surveillance; Immunohistochemistry; Innate immunity; Surfactant protein D; Tumor microenvironment; Immunology and Allergy; Immunologylcsh:RC581-607Ovarian cancer
researchProduct

Genome-wide associations for birth weight and correlations with adult disease

2016

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10(-8)). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genet…

Male0301 basic medicineNetherlands Twin Register (NTR)AgingDatasets as TopicPhysiologyBlood PressureGenome-wide association studyCoronary Artery DiseaseType 2 diabetesBioinformaticsCHARGE Consortium Hematology Working GroupCohort Studies0302 clinical medicineBirth WeightInsulinGlucose homeostasis030212 general & internal medicineeducation.field_of_studyMultidisciplinaryAnthropometry3. Good healthPhenotype/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingFemaleGlycogenSignal TransductionAdulthypertensionGenotypeGeneral Science & TechnologyBirth weightintrauterine growthPopulationQuantitative trait locusBiologyArticlequantitative traitGenomic Imprinting03 medical and health sciencesFetusSDG 3 - Good Health and Well-beingEarly Growth Genetics (EGG) ConsortiumMD MultidisciplinaryGenetic variation/dk/atira/pure/keywords/cohort_studies/netherlands_twin_register_ntr_medicineHumansmetabolic disordersGenetic Predisposition to DiseaseeducationgenomeGenetic associationGenetic Variationbirth weightta3121Chromatin Assembly and Disassemblymedicine.diseaseta3123Glucose030104 developmental biologyDiabetes Mellitus Type 2Genetic Locigenome-wide association studiesadult diseaseGenome-Wide Association Study
researchProduct