Search results for "predictive"

showing 10 items of 1373 documents

Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B…

2016

Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) focuses on the integrated care of chronic diseases. Area 5 (Care Pathways) was initiated using chronic respiratory diseases as a model. The chronic respiratory disease action plan includes (1) AIRWAYS integrated care pathways (ICPs), (2) the joint initiative between the Reference site MACVIA-LR (Contre les MAladies Chroniques pour un VIeillissement Actif) and ARIA (Allergic Rhinitis and its Impact on Asthma), (3) Commitments for Action to the European Innovation Partnership on Active and Healthy Ageing and the AIRWAYS ICPs network. It is deployed in collaboration with the World Health Organizatio…

Pulmons -- Malalties obstructivesVeterinary medicineAllergyPublished ErratumLANGUEDOC-ROUSSILLONAllergyRespiratory Medicine and Allergy[SDV]Life Sciences [q-bio]Aparell respiratori -- MalaltiesOPERATIONAL DEFINITIONAlternative medicineReviewChronic respiratory diseasesGLOBAL ALLIANCESYSTEMS MEDICINE0302 clinical medicineMedicine and Health SciencesImmunology and AllergyMACVIA030212 general & internal medicineAIRWAYS ICPLungmedicin och allergiEIP on AHA; European Innovation Partnership on Active and Healthy Ageing; Chronic respiratory diseases; AIRWAYS ICPs; MACVIA; ARIA; Scaling upGINA STRATEGYAIRWAYSUPDATE ARIA 2008Scaling upRespiratory disease:Outras Ciências Agrárias [Ciências Agrárias]3. Good healthChronic respiratory diseaseALLERGIC RHINITISICPsAIRWAYS ICPsGeneral partnershipAction planErratumLife Sciences & BiomedicineAIRWAYS ICPs; ARIA; Chronic respiratory diseases; EIP on AHA; European Innovation Partnership on Active and Healthy Ageing; MACVIA; Scaling upPulmonary and Respiratory Medicinemedicine.medical_specialtyEIP on AHAAIRWAYS ICPs; ARIA; Chronic respiratory diseases; EIP on AHA; European Innovation Partnership on Active and Healthy Ageing; MACVIA; Scaling up; Immunology and AllergyEmerging technologiesImmunologyREFERENCE SITESocio-culturalePredictive medicine03 medical and health sciencesEuropean Innovation Partnership on Active and Healthy AgeingNursingCritical success factorJournal Articlemedicineddc:610Science & TechnologyARIAbusiness.industrySettore MED/09 - MEDICINA INTERNAAIRWAYS-ICPSmedicine.diseaseIntegrated careAlliance030228 respiratory systemCiências Agrárias::Outras Ciências Agrárias3121 General medicine internal medicine and other clinical medicineFamily medicineImmunologyHealthy ageingbusinessSEVERE ASTHMA
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Potential Biomarkers Associated with Multiple Sclerosis Pathology

2021

Multiple sclerosis (MS) is a complex disease of the central nervous system (CNS) that involves an intricate and aberrant interaction of immune cells leading to inflammation, demyelination, and neurodegeneration. Due to the heterogeneity of clinical subtypes, their diagnosis becomes challenging and the best treatment cannot be easily provided to patients. Biomarkers have been used to simplify the diagnosis and prognosis of MS, as well as to evaluate the results of clinical treatments. In recent years, research on biomarkers has advanced rapidly due to their ability to be easily and promptly measured, their specificity, and their reproducibility. Biomarkers are classified into several categor…

QH301-705.5diagnosticInflammationReviewBioinformaticsmultiple sclerosisCatalysisInorganic ChemistryBlood serummedicineHumanspredictivePhysical and Theoretical ChemistryRemyelinationbiomarkers diagnostic multiple sclerosis predictive prognosis treatment response monitoringBiology (General)Molecular BiologyPathologicalQD1-999SpectroscopyInflammationbusiness.industryMultiple sclerosisOrganic ChemistryNeurodegenerationReproducibility of ResultsbiomarkersGeneral Medicinemedicine.diseaseComputer Science ApplicationsChemistrymedicine.anatomical_structureGliosisDisease ProgressionBiomarker (medicine)prognosismedicine.symptombusinesstreatment response monitoringInternational Journal of Molecular Sciences
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The role of the reporting framework MIATA within current efforts to advance immune monitoring

2014

Quality Controlmedicine.medical_specialtyLaboratory Proficiency TestingConsensusmedicine.medical_treatmentInternational CooperationT-LymphocytesImmunologyImmune monitoringPharmacologyImmunologic TestsImmune assaysMonitoring ImmunologicPredictive Value of TestsmedicineImmunology and AllergyHumansCooperative BehaviorIntensive care medicineImmune monitoringObserver Variationbusiness.industryGuideline adherenceMIATAImmunologic TestsReproducibility of ResultsImmunotherapyTreatment OutcomeReportingPredictive value of testsPractice Guidelines as TopicCooperative behaviorLaboratory Proficiency TestingGuideline AdherenceImmunotherapyCurrent (fluid)businessLaboratories
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An AMI System for User Daily Routine Recognition and Prediction

2014

Ambient Intelligence (AmI) defines a scenario involving people living in a smart environment enriched by pervasive sensory devices with the goal of assisting them in a proactive way to satisfy their needs. In a home scenario, an AmI system controls the environment according to a user’s lifestyle and daily routine. To achieve this goal, one fundamental task is to recognize the user’s activities in order to generate his daily activities profile. In this chapter, we present a simple AMI system for a home scenario to recognize and predict users’ activities. With this predictive capability, it is possible to anticipate their actions and improve their quality of life. Our approach uses a Hidden M…

Quality of lifeSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniAmbient intelligenceActivities of daily livingbusiness.industryComputer scienceSystem controlSmart environmentSensory informationData scienceTask (project management)Knowledge baseActivity recognitionQuality of lifeKnowledge baseHome automationHuman–computer interactionDaily activityAmbient intelligenceSmart environmentPredictive capabilitieHidden Markov modelbusiness
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Biopartitioning micellar chromatoraphy to predict blood to lung, blood to liver, blood to fat and blood to skin partition coefficients of drugs

2009

[EN] Biopartitioning micellar chromatography (BMC), a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 in adequate experimental conditions, has demonstrated to be useful in mimicking the drug partitioning process into biological systems. In this paper, the usefulness of BMC for predicting the partition coefficients from blood to lung, blood to liver. blood to fat and blood to skin is demonstrated. PLS2 and multiple linear regression (MLR) models based on BMC retention data are proposed and compared with other ones reported in bibliography. The proposed models present better or similar descriptive and predictive capability. (C) 2008 Elsevier B.V. All rights r…

Quantitative structure–activity relationshipBlood to skinQuantitative Structure-Activity RelationshipPredictive capabilityPartition coefficientsBiochemistryAnalytical ChemistryPharmacokineticsBlood to lungLinear regressionQUIMICA ANALITICAmedicineAnimalsHumansEnvironmental ChemistryPharmacokineticsTissue DistributionLungMicellesSpectroscopySkinLungChromatographyChemistryComputational BiologyChromatography liquidBiopartitioning micellar chromatographyRatsPartition coefficientmedicine.anatomical_structureAdipose TissueLiverPharmaceutical PreparationsMicellar liquid chromatographyLinear ModelsBlood to fatRabbitsChromatography LiquidBlood to liver
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Use of molecular topology for the prediction of physico-chemical, pharmacokinetic and toxicological properties of a group of antihistaminic drugs

2002

We used molecular connectivity to search mathematical models for predicting physico-chemical (e.g. the partition coefficient, P), pharmacokinetic (e.g. the time of maximum plasma level, and toxicological properties (lethal dose, LD) for a group of antihistaminic drugs. The results obtained clearly reveal the high efficiency of molecular topology for the prediction of these properties. Randomization and cross-validation by use of leave-one-out tests were also performed in order to assess the stability and the prediction ability of the connectivity functions selected.

Quantitative structure–activity relationshipChemistryQuantitative Structure-Activity RelationshipPharmaceutical SciencePlasma levelsPharmacologyModels BiologicalLethal Dose 50Structure-Activity RelationshipPharmacokineticsPredictive Value of TestsHistamine H1 AntagonistsRegression AnalysisAntihistaminic drugsMolecular topologyBiological systemInternational Journal of Pharmaceutics
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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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Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity.

2013

The concept of molecular similarity is one of the most central in the fields of predictive toxicology and quantitative structure-activity relationship (QSAR) research. Many toxicological responses result from a multimechanistic process and, consequently, structural diversity among the active compounds is likely. Combining this knowledge, we introduce similarity boosted QSAR modeling, where we calculate molecular descriptors using similarities with respect to representative reference compounds to aid a statistical learning algorithm in distinguishing between different structural classes. We present three approaches for the selection of reference compounds, one by literature search and two by…

Quantitative structure–activity relationshipInformaticsbusiness.industryStatistical learningGeneral Chemical EngineeringStructural diversityQuantitative Structure-Activity RelationshipPattern recognitionGeneral ChemistryPredictive toxicologyLibrary and Information Sciencescomputer.software_genreToxicologyComputer Science ApplicationsSimilarity (network science)Molecular descriptorArtificial intelligenceData miningbusinessCluster analysiscomputerMathematicsJournal of chemical information and modeling
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A topological substructural approach for the prediction of P-glycoprotein substrates

2006

A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the predictio…

Quantitative structure–activity relationshipMolecular modelLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisTopologyModels BiologicalData setSet (abstract data type)Pharmaceutical PreparationsPredictive Value of TestsTest setLinear ModelsComputer SimulationATP Binding Cassette Transporter Subfamily B Member 1Sensitivity (control systems)FluoroquinolonesMathematicsJournal of Pharmaceutical Sciences
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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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