Search results for "predictive"

showing 10 items of 1373 documents

Statistical Analysis of a Method to Predict Drug–Polymer Miscibility

2015

In this study, a method proposed to predict drug-polymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as "transformation to linearity," which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that t…

PolymersChemistry PharmaceuticalPharmaceutical Science02 engineering and technology030226 pharmacology & pharmacyMiscibility03 medical and health sciences0302 clinical medicineMinimum-variance unbiased estimatorPredictive Value of TestsStatisticsStatistical inferenceApplied mathematicsMathematicsCalorimetry Differential ScanningFelodipineTemperatureLinear modelEstimatorModels Theoretical021001 nanoscience & nanotechnologyConfidence intervalTransformation (function)Experimental uncertainty analysisPharmaceutical PreparationsSolubilityLinear ModelsThermodynamics0210 nano-technologyAlgorithmsJournal of Pharmaceutical Sciences
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A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Popu…

2021

Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models wer…

PopulationMachine learningcomputer.software_genreLogistic regressionPediatricsProcalcitoninRJ1-570Medicinerisk factorseducationOriginal Researcheducation.field_of_studyKawasaki diseasebusiness.industryRetrospective cohort studyNomogrammedicine.diseaseSupport vector machineprediction modelmachine learningPediatrics Perinatology and Child HealthKawasaki diseaseArtificial intelligencebusinesscomputerintravenous immunoglobulin resistancePredictive modellingFrontiers in Pediatrics
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Catheter venography for the assessment of internal jugular veins and azygous vein: position statement by expert panel of the International Society fo…

2013

This document by an expert panel of the International Society for Neurovascular Disease is aimed at presenting current technique and interpretation of catheter venography of the internal jugular veins, azygous vein and other veins draining the central nervous system. Although interventionalists agree on general rules, significant differences exist in terms of details of venographic technique and interpretations of angiographic pictures. It is also suggested that debatable findings should be investigated using multimodal diagnostics. Finally, the authors recommend that any publication on chronic cerebrospinal venous insufficiency should include detailed description of venographic technique u…

Position statementmedicine.medical_specialtyCatheterization Central VenousEndovascular therapyVenographyConstriction Pathologicmultiple sclerosisRisk Assessmentneurovascular interventionsPredictive Value of TestsmedicineHumansVascular Diseasesvascular malformationsUltrasonography Interventionalmedicine.diagnostic_testbusiness.industryPhlebographyNeurovascular bundlemedicine.diseasePrognosisCerebral VeinsCatheterAzygous veinChronic cerebrospinal venous insufficiencyCerebrovascular DisordersChronic diseaseVenous InsufficiencyAzygos VeinChronic Diseasecardiovascular systemRadiologyUltrasonographyJugular VeinsCardiology and Cardiovascular MedicinebusinessVASA. Zeitschrift fur Gefasskrankheiten
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Coping strategies and postpartum depressive symptoms: A structural equation modelling approach.

2014

AbstractBackgroundVariables such as the mother's personality, social support, coping strategies and stressful events have been described as risk factors for postpartum depression. Structural Equation Modelling (SEM) analysis was used to examine whether neuroticism, perceived social support, perceived life events, and coping strategies are associated with postpartum depressive symptoms at the 8th and 32nd weeks.MethodsA total of 1626 pregnant women participated in a longitudinal study. Different evaluations were performed 8 and 32 weeks after delivery. Several measures were used: the Edinburgh Postnatal Depression Scale (EPDS), the Diagnostic Interview for Genetic Studies (DIGS), the Eysenck…

Postpartum depressionAdultCoping (psychology)Longitudinal studymedia_common.quotation_subjectStatistics as TopicPsychological TechniquesPersonality AssessmentDepression PostpartumLife Change EventsSocial supportPredictive Value of TestsPregnancyRisk FactorsAdaptation PsychologicalmedicinePersonalityHumansLongitudinal Studiesmedia_commonNeuroticismPostpartum PeriodSocial Supportmedicine.diseasePrognosisNeuroticismAnxiety DisordersEysenck Personality QuestionnairePsychiatry and Mental healthEdinburgh Postnatal Depression ScaleFemalePsychologyStress PsychologicalClinical psychologyEuropean psychiatry : the journal of the Association of European Psychiatrists
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A cost model for the selection of a maintenance activity in a series system

2012

Predictive Maintenance Series Systems Cost Function Maintenance Scheduling
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Symptoms and the body: Taking the inferential leap

2017

The relationship between the conscious experience of physical symptoms and indicators of objective physiological dysfunction is highly variable and depends on characteristics of the person, the context and their interaction. This relationship often breaks down entirely in the case of "medically unexplained" or functional somatic symptoms, violating the basic assumption in medicine that physical symptoms have physiological causes. In this paper, we describe the prevailing theoretical approach to this problem and review the evidence pertaining to it. We then use the framework of predictive coding to propose a new and more comprehensive model of the body-symptom relationship that integrates ex…

Predictive codingConsciousnessCognitive Neurosciencemedia_common.quotation_subject: Neurosciences & comportement [H07] [Sciences sociales & comportementales psychologie]Medically unexplainedContext (language use)Bayesian030227 psychiatryDevelopmental psychologyInteroception03 medical and health sciencesBehavioral NeuroscienceVariable (computer science)0302 clinical medicineNeuropsychology and Physiological PsychologySymptom perceptionCurrent theoryHumans: Neurosciences & behavior [H07] [Social & behavioral sciences psychology]ConsciousnessPsychology030217 neurology & neurosurgeryCognitive psychologymedia_common
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Context-dependent minimisation of prediction errors involves temporal-frontal activation

2020

According to the predictive coding model of perception, the brain constantly generates predictions of the upcoming sensory inputs. Perception is realised through a hierarchical generative model which aims at minimising the discrepancy between predictions and the incoming sensory inputs (i.e., prediction errors). Notably, prediction errors are weighted depending on precision of prior information. However, it remains unclear whether and how the brain monitors prior precision when minimising prediction errors in different contexts. The current study used magnetoencephalography (MEG) to address this question. We presented participants with repetition of two non-predicted probes embedded in cont…

Predictive codingMaleComputer sciencehavaitseminen0302 clinical medicineMagnetoencephalography (MEG)Attentionpredictive codingmedia_commonParametric statisticsMEGmedicine.diagnostic_test05 social sciencesBrainMagnetoencephalographyElectroencephalographyTemporal Lobeauditory perceptionGenerative modelNeurologyrepetition enhancementAuditory PerceptionEvoked Potentials AuditoryFemaleAdultAuditory perceptionCognitive Neurosciencemedia_common.quotation_subjectSensory systemStimulus (physiology)kuulohavainnot050105 experimental psychologyLateralization of brain functionlcsh:RC321-571Young Adult03 medical and health sciencesRepetition suppressionPerceptionmedicineHumansmagnetoencephalography (MEG)0501 psychology and cognitive sciencesRepetition enhancementlcsh:Neurosciences. Biological psychiatry. NeuropsychiatryAuditory Cortexbusiness.industryPattern recognitionMagnetoencephalographyWeightingrepetition suppressionArtificial intelligencebusiness030217 neurology & neurosurgeryNeuroImage
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A predictive function optimization algorithm for multi-spectral skin lesion assessment

2015

The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improv…

Predictive functionRate of convergenceOptimization algorithmComputer scienceGenetic algorithmProcess (computing)Function (mathematics)Parallel computingField-programmable gate arraySkin lesionAlgorithm2015 23rd European Signal Processing Conference (EUSIPCO)
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Concordance of Radiological, Laparoscopic and Laparotomic Scoring to Predict Complete Cytoreduction in Women with Advanced Ovarian Cancer

2023

Objective: To identify the best method among the radiologic, laparoscopic and laparotomic scoring assessment to predict the outcomes of cytoreductive surgery in patients with advanced ovarian cancer (AOC). Methods: Patients with AOC who underwent pre-operative computed tomography (CT) scan, laparoscopic evaluation, and cytoreductive surgery between August 2016 and February 2021 were retrospectively reviewed. Predictive Index (PI) score and Peritoneal Cancer Index (PCI) scores were used to estimate the tumor load and predict the residual disease in the primary debulking surgery (PDS) and interval debulking surgery (IDS) after neoadjuvant chemotherapy (NACT) groups. Concordance percentages we…

Predictive index scoreCancer ResearchOncologyOvarian cancerPrediction modelCytoreductive surgeryPrimary debulking surgery.Interval debulking surgeryNeoadjuvant chemotherapyPeritoneal cancer index scoreSettore MED/40 - Ginecologia E Ostetriciaovarian cancer; cytoreductive surgery; prediction model; predictive index score; peritoneal cancer index score; primary debulking surgery; interval debulking surgery; neoadjuvant chemotherapyCancers
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Probabilistic inference of approximations

2006

We consider probabilistic inductive inference of Godel numbers of total recursive functions when the set of possible errors is allowed to be infinite, but with bounded density. We have obtained hierarchies of classes of functions identifiable with different probabilities up to sets with fixed density. The obtained hierarchies turn out to be different from those which we have in the case of exact identification.

Predictive inferenceProbabilistic logic networkFrequentist inferenceProbabilistic CTLProbabilistic logicFiducial inferenceStatistical inferenceApplied mathematicsVariable eliminationMathematics
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