Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Models and methods for supporting lot sizing decisions in product recovery systems

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2011

Approximations of the Fisher information for the construction of efficient experimental designs in nonlinear mixed effects models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2012

Applicability of Two International Risk Scores in Cardiac Surgery in a Reference Center in Brazil

Background:The applicability of international risk scores in heart surgery (HS) is not well defined in centers outside of North America and Europe.Objective:To evaluate the capacity of the Parsonnet Bernstein 2000 (BP) and EuroSCORE (ES) in predicting in-hospital mortality (IHM) in patients undergoing HS at a reference hospital in Brazil and to identify risk predictors (RP).Methods:Retrospective cohort study of 1,065 patients, with 60.3% patients underwent coronary artery bypass grafting (CABG), 32.7%, valve surgery and 7.0%, CABG combined with valve surgery. Additive and logistic scores models, the area under the ROC (Receiver Operating Characteristic) curve (AUC) and the standardized mortality ratio (SMR) were calculated. Multivariate logistic regression was performed to identify the RP.Results:Overall mortality was 7.8%. The baseline characteristics of the patients were significantly different in relation to BP and ES. AUCs of the logistic and additive BP were 0.72 (95% CI, from 0.66 to 0.78 p = 0.74), and of ES they were 0.73 (95% CI; 0.67 to 0.79 p = 0.80). The calculation of the SMR in BP was 1.59 (95% CI; 1.27 to 1.99) and in ES, 1.43 (95% CI; 1.14 to 1.79). Seven RP of IHM were identified: age, serum creatinine > 2.26 mg/dL, active endocarditis, systolic pulmonary arterial pressure > 60 mmHg, one or more previous HS, CABG combined with valve surgery and diabetes mellitus.Conclusion:Local scores, based on the real situation of local populations, must be developed for better assessment of risk in cardiac surgery.

Statistical analysis in multivariate sampling

Magdeburg, Univ., Fak. für Mathematik, Diss., 2011

Multivariate Analysis for Animal Selection in Experimental Research

Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

Metabolic Syndrome and Importance of Associated Variables in Children and Adolescents in Guabiruba - SC, Brazil

Background:The risk factors that characterize metabolic syndrome (MetS) may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR), in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children). Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48%) and obese (41%) students when compared with eutrophic individuals (11%; p = 0.034). The variables with greatest influence on the development of MetS were obesity (OR = 32.7), overweight (OR = 6.1), IR (OR = 4.4; p ≤ 0.0001 for all) and age (OR = 1.15; p = 0.014).Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.

Advancing the understanding of brain function with multivariate pattern analysis

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

Simulation of interacting populations in inhomogeneous flows using reduced models

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

Conversive Hidden non-Markovian models

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Analysis and numerical investigation of dynamic models for liquid chromatography

Magdeburg, Univ., Fak. für Mathematik, Diss., 2013

Subjektive Vaterschaftskonzepte und ihre Determinanten in drei Familienentwicklungsphasen : eine latente Profilanalyse multipler Gruppen und multivariate Untersuchung verschiedener Determinanten

Magdeburg, Univ., Fak. für Humanwiss., Diss., 2013

Mathematical models of influenza A virus infection : from intracellular replication to virus growth in cell populations

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2015