Search results for " Receiver operating characteristic"

showing 10 items of 10 documents

Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.

2021

Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…

0301 basic medicineSimeprevirArtificial intelligencevirusesMERS Middle East Respiratory SyndromeHealth InformaticsBiologyMachine learningcomputer.software_genremedicine.disease_causeAntiviral AgentsArticleWHO World Health OrganizationAUC area under the curve03 medical and health sciences0302 clinical medicinessRNA single-stranded RNA virusmedicineChemotherapyHumansSARS severe acute respiratory syndromeCOVID-19 coronavirus disease 2019CoronavirusNatural productsVirtual screeningACE2 angiotensin converting enzyme 2Drug discoverybusiness.industrySARS-CoV-2COVID-19LBE lowest binding energyFDA Food and Drug AdministrationROC receiver operating characteristicComputer Science ApplicationsHIV human immunodeficiency virusMolecular Docking SimulationDrug repositioning030104 developmental biologyDrug developmentSevere acute respiratory syndrome-related coronavirusParitaprevirInfectious diseasesRespiratory virusArtificial intelligenceSupervised Machine Learningbusinesscomputer030217 neurology & neurosurgeryComputers in biology and medicine
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Evaluation of serum s-IgE/total IgE ratio in predicting clinical response to allergen-specific immunotherapy.

2009

Background: To date, no predictive tests for the clinical response to allergen-specific immunotherapy (ASI) are available. Therefore an in vivo or in vitro test would be of great value. Objective: We sought to evaluate pretreatment parameters used in diagnosing allergic rhinitis and determining serum specific IgE (s-IgE) levels, serum total IgE (t-IgE) levels, and blood eosinophil counts and to identify whether can be used to predict clinical improvement in monosensitized patients with allergic rhinitis with or without asthma treated with immunotherapy. Methods:We analyzed 279 patients who had undergone 4 years of ASI administered either by means of the subcutaneous immunotherapy (76 patien…

AdultMaleAllergySettore MED/09 - Medicina InternaRhinitis Allergic PerennialAdolescentmedicine.medical_treatmentImmunologyspecific IgEImmunoglobulin Eblood eosinophil countsYoung AdultBlood serummedicineImmunology and AllergyHumansreceiver operating characteristic curveAsthmaDesensitization (medicine)Retrospective StudiesSkin Testsserum s-IgE/total IgE ratio; allergen-specific immunotherapyHouse dust miteserum s-IgE/total IgE ratiobiologyserum-specific IgE/serum total IgE ratiobusiness.industryAllergen-specific immunotherapy; blood eosinophil counts; receiver operating characteristic curve; serum-specific IgE/serum total IgE ratio; specific IgE; total IgEArea under the curveImmunotherapyAllergensImmunoglobulin EMiddle Agedmedicine.diseasebiology.organism_classificationPrognosisAllergen-specific immunotherapyBlood Cell Counttotal IgEEosinophilsTreatment OutcomeDesensitization ImmunologicSpirometryImmunologybiology.proteinFemalebusiness
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Differences and Similarities between Allergic and Nonallergic Rhinitis in a Large Sample of Adult Patients with Rhinitis Symptoms

2010

<i>Background:</i> Allergic rhinitis (AR) and nonallergic rhinitis (NAR) may present with different clinical and laboratory characteristics. <i>Methods:</i> A total of 1,511 consecutive patients, aged 18–81 years, diagnosed with rhinitis, 56% females and 44% males, underwent complete allergic evaluation including skin prick test, blood eosinophil counts, nasal eosinophil counts, peak nasal inspiratory flow (PNIF) measurement and evaluation of nasal symptoms using a visual analog scale (VAS). <i>Results:</i> A total of 1,107 patients (73%)had AR, whereas 404 (27%) had NAR. Patients with NAR were older and predominantly female. A higher nasal eosinophils co…

AdultMaleNasal eosinophilAgingAllergyRhinitis Allergic PerennialSkin prick testPeak nasal inspiratory flowAdolescentNon allergic rhinitisVisual analogue scaleNon-allergic rhinitisImmunologyHistamine AntagonistsReceiver operating characteristicSettore MED/42 - Igiene Generale E ApplicataSeverity of Illness IndexAllergic rhinitisYoung AdultSex FactorsNonallergic rhinitisBlood eosinophilAllergic rhinitis; Non allergic rhinitis; Skin prick test; Peak nasal inspiratory flow; Blood eosinophil; Nasal eosinophil; Visual analog scale; Receiver operating characteristicHumansImmunology and AllergyMedicineAllergic rhinitis Non allergic rhinitis Skin prick test Peak nasal inspiratory flow Blood eosinophil Nasal eosinophil Visual analog scale Receiver operating characteristicVisual analog scaleYoung adultAgedRhinitisSkin TestsAged 80 and overAdult patientsbusiness.industryHeadacheGeneral MedicineMiddle AgedEosinophilConjunctivitismedicine.diseaseLarge sampleEosinophilsmedicine.anatomical_structureSettore MED/31 - OtorinolaringoiatriaImmunologyFemaleNasal Obstructionbusiness
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Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms and the development of the software A…

2014

Background. This thesis consist of parts(i)Introduction in wich we present the clinical problem of rhinitis;(ii)the methods to evaluate the diagnostic choises;(iii)the rational errors in Allergy,(iv)the experimental part of thesis with wich we developed the software ARTSTAT,wich is the application of the analysis reported.Objective: We studied the ability of the logistic regression model obtained by the evaluaqtion of a database, to detect patients with positive allergy skin prick test(SPT)and patients with negative SPT. The model developed was valitated using the data set obtained from another medical institution. Methods: The analysis was carried out using a database obtained from a quest…

Allergic rhinitis Nonallergic rhinitis Decision Matrix Logistic regression model Receiver Operating Characteristic curve probability Diagnostic decision making nasal symptom Skin prick test (SPT) Cognitive Errors
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Prediction of type 2 diabetes mellitus based on nutrition data

2021

Abstract Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013–14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to bu…

Elastic net regularizationFood intakeMultivariate statistics24HFL 24-h food listEndocrinology Diabetes and MetabolismPopulation030209 endocrinology & metabolismType 2 diabetesLogistic regression03 medical and health sciences0302 clinical medicinePredictive Value of TestsRisk FactorsElastic net regressionPrediction modelGermanyStatisticsmedicineHumans030212 general & internal medicineeducationNutritionMathematicseducation.field_of_studyNutrition and DieteticsReceiver operating characteristicDietary Surveys and Nutritional EpidemiologyType 2 Diabetes MellitusType 2 diabetesT2DM type 2 diabetes mellitusmedicine.diseasePPV positive predictive valueDietROC receiver operating characteristicCross-Sectional StudiesNPV negative predictive valueDiabetes Mellitus Type 2ROC CurveKORA Cooperative Health Research in the Region of Augsburg24hfl 24-h Food List ; Elastic Net Regression ; Kora Cooperative Health Research In The Region Of Augsburg ; Npv Negative Predictive Value ; Nutrition ; Ppv Positive Predictive Value ; Prediction Model ; Roc Receiver Operating Characteristic ; T2dmResearch ArticleFood ScienceJournal of Nutritional Science
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Dysfunction of attention switching networks in amyotrophic lateral sclerosis

2019

Objective To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms. Rationale The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pathological impairment of the neural network components which generate these functions. Source localisation can mitigate the poor spatial resolution of sensor-level EEG analysis by associating the sensor-level signals to the contributing brain sources. The functional activity in each generating source can therefore be individually measured and investigat…

MaleMismatch negativitySource localisationEEG ElectroencephalographyMismatch negativityNetworkElectroencephalographylcsh:RC346-429PET Positron emission tomographyCognition0302 clinical medicineC9orf72AttentionEEGAUROC Area under receiver operating characteristic curveAmyotrophic lateral sclerosisAged 80 and overmedicine.diagnostic_test05 social sciencesCognitive flexibilityBrainRegular ArticleElectroencephalographyCognitionMiddle AgedSTG Superior temporal gyrusNeurologyMTG Mid temporal gyrusDLPFC Dorsolateral prefrontal cortexlcsh:R858-859.7FemaleLCMV Linearly constrained minimum varianceIFG Inferior frontal gyrusAdultCognitive Neurosciencelcsh:Computer applications to medicine. Medical informatics050105 experimental psychologyCWIT Colour-word interference test03 medical and health sciencesfMRI Functional magnetic resonance imagingMEG MagnetoencephalographymedicineMMN Mismatch negativityHumans0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imagingLS Amyotrophic Lateral SclerosisAAL Automated Anatomical Labellinglcsh:Neurology. Diseases of the nervous systemAEP Auditory evoked potentialAgedbusiness.industryAmyotrophic Lateral SclerosisIQR Interquartile rangeNeurophysiologyqEEG Quantitative EEGmedicine.diseaseNeurology (clinical)Nerve NetFunctional magnetic resonance imagingbusinessNeuroscience030217 neurology & neurosurgeryeLORETA Exact low-resolution brain electromagnetic tomographyNeuroImage: Clinical
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Determining a healthy reference range and factors potentially influencing PRO-C3 – A biomarker of liver fibrosis

2021

Background & Aims Progressive fibrosis has been identified as the major predictor of mortality in patients with non-alcoholic fatty liver disease (NAFLD). Several biomarkers are currently being evaluated for their ability to substitute the liver biopsy as the reference standard. Recent clinical studies in NAFLD/NASH patients support the utility of PRO-C3, a marker of type III collagen formation, as a marker for the degree of fibrosis, disease activity, and effect of treatment. Here we establish the healthy reference range, optimal sample handling conditions for both short- and long-term serum storage, and robustness for the PRO-C3 assay. Methods PRO-C3 was measured in 269 healthy volunteers…

NASH-CRN NASH Clinical Research NetworkBiopsyDiseaseAST aspartate aminotransferaseRC799-869Ethnic groupsGastroenterologyNIMBLE Non-Invasive Biomarkers of Metabolic Liver Disease (consortium)FibrosisImmunology and AllergyBody mass indexmedicine.diagnostic_testFatty liverNAS NAFLD Activity ScoreGastroenterologyDiseases of the digestive system. GastroenterologyHospitalsNPV negative predictive valueLiver biopsyBiomarker (medicine)Research Articlemedicine.medical_specialtyNAFLD non-alcoholic fatty liver diseaseADAM A Disintegrin and MetalloproteasesNASH non-alcoholic steatohepatitisReference rangeReference valuesAUROC area under the receiver operating characteristics curveInternal medicineALT alanine aminotransferaseBiopsyInternal MedicinemedicineHumansFIB-4 fibrosis-4Healthy volunteersHepatologyALP alkaline phosphatasebusiness.industryCLSI Clinical and Laboratory Standards InstituteT2DM type 2 diabetes mellitusELF™ test Enhanced Liver Fibrosis testmedicine.diseaseLITMUS Liver Investigation: Testing Marker Utility in Steatohepatitis (consortium)Collagen type IIIFibrosisPPV positive predictive valueReference standardsbusinessBody mass indexBiomarkersNon-alcoholic fatty liver disease
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Vasoactive peptide urotensin II in plasma is associated with cerebral vasospasm after aneurysmal subarachnoid hemorrhage and constitutes a potential …

2019

National audience; OBJECTIVECerebral vasospasm (VS) is a severe complication of aneurysmal subarachnoid hemorrhage (SAH). Urotensin II (UII) is a potent vasoactive peptide activating the urotensin (UT) receptor, potentially involved in brain vascular pathologies. The authors hypothesized that UII/UT system antagonism with the UT receptor antagonist/biased ligand urantide may be associated with post-SAH VS. The objectives of this study were 2-fold: 1) to leverage an experimental mouse model of SAH with VS in order to study the effect of urotensinergic system antagonism on neurological outcome, and 2) to investigate the association between plasma UII level and symptomatic VS after SAH in huma…

SAPS II = Simplified Acute Physiology Score IIMCA = middle cerebral arteryAUC = area under the curvesubarachnoid hemorrhage[SDV]Life Sciences [q-bio]ICU = intensive care unitUT = urotensin (receptor)vascular disordersintensive care unitUII = urotensin IIcardiovascular diseaseshumanmouseWFNS = World Federation of Neurosurgical SocietiesEVD = external ventricular drainageACA = anterior cerebral arteryurotensin IInervous system diseasesSAH = subarachnoid hemorrhageSE = standard errorROC = receiver operating characteristic[SDV] Life Sciences [q-bio]cerebral vasospasmVS = vasospasmDCI = delayed cerebral ischemiaCSF = cerebrospinal fluidIRB = institutional review boardmRS = modified Rankin ScaleIQR = interquartile range
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Increased serum miR-193a-5p during non-alcoholic fatty liver disease progression: Diagnostic and mechanistic relevance

2022

Background & Aims Serum microRNA (miRNA) levels are known to change in non-alcoholic fatty liver disease (NAFLD) and may serve as useful biomarkers. This study aimed to profile miRNAs comprehensively at all NAFLD stages. Methods We profiled 2,083 serum miRNAs in a discovery cohort (183 cases with NAFLD representing the complete NAFLD spectrum and 10 population controls). miRNA libraries generated by HTG EdgeSeq were sequenced by Illumina NextSeq. Selected serum miRNAs were profiled in 372 additional cases with NAFLD and 15 population controls by quantitative reverse transcriptase PCR. Results Levels of 275 miRNAs differed between cases and population controls. Fewer differences were seen wi…

SCORING SYSTEMCPM counts per millionAUROC area under the receiver operating characteristicRC799-869AST aspartate aminotransferaseMicroRNA; Non-alcoholic fatty liver disease; Biomarker; SequencingTGF-β transforming growth factor-betaGastroenterologySTEATOHEPATITISLiver disease0302 clinical medicineFibrosismiRNA microRNAlogFC log2 fold changeFIBROSISImmunology and AllergySequencing0303 health scienceseducation.field_of_studyNAS NAFLD activity scoremedicine.diagnostic_testFatty liverGastroenterologyGTEx Genotype-Tissue ExpressionMicroRNADiseases of the digestive system. Gastroenterology3. Good healthReal-time polymerase chain reactionBiomarker MicroRNA Non-alcoholic fatty liver disease SequencingLiver biopsyACIDBiomarker (medicine)030211 gastroenterology & hepatologyLife Sciences & BiomedicineResearch ArticleEXPRESSIONmedicine.medical_specialtyNAFLD non-alcoholic fatty liver diseaseNASH non-alcoholic steatohepatitisPopulationGastroenterology and HepatologySAF steatosis–activity–fibrosisVALIDATIONER endoplasmic reticulum03 medical and health sciencescDNA complementary DNAInternal medicineALT alanine aminotransferaseGastroenterologiInternal MedicinemedicineNAFL non-alcoholic fatty liverALGORITHMFIB-4 fibrosis-4education030304 developmental biologyPCA principal component analysisScience & TechnologyGastroenterology & HepatologyHepatologybusiness.industryBiomarkerFC fold changemedicine.diseaseBiomarker; MicroRNA; Non-alcoholic fatty liver disease; Sequencingdigestive system diseasesFLIP fatty liver inhibition of progressionCt cycle thresholdSteatosisqPCR quantitative PCRbusinessNon-alcoholic fatty liver disease
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Validation procedures in radiological diagnostic models. Neural network and logistic regression

1999

The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validatio…

Validation methodsReceiver operating characteristicArtificial neural networkComputer scienceRadiological weaponResamplingSkull neoplasms logistic regression neural networks receiver operating characteristic curve statistics resamplingStatisticsWord error ratejel:C13Logistic regressionCross-validationjel:C14
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