Tesis sobre el tema "Medicine – Mathematical models"
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Campanelli, Mark Benjamin. "Multicellular mathematical models of somitogenesis". Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/campanelli/CampanelliM0809.pdf.
Texto completoStekel, Dov Joseph. "Mathematical models of immune system and virus dynamics". Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364143.
Texto completoCLOUGH, ANNE VIRGINIA. "A MATHEMATICAL MODEL OF SINGLE-PHOTON EMISSION COMPUTED TOMOGRAPHY (RADON TRANSFORM, COMPTON SCATTER, ATTENUATION, NUCLEAR MEDICINE)". Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/188142.
Texto completoOrme, Michelle Elaine. "The vascularization of solid tumours : mathematical models of tumour angiogenesis and vascular tumour growth". Thesis, University of Bath, 1996. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362238.
Texto completoKnight, Peter Robin. "Artificial intelligence and mathematical models for intelligent management of aircraft data". Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/355717/.
Texto completoPowell, Megan Olivia. "Mathematical Models of the Activated Immune System During HIV Infection". University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1301415627.
Texto completoCargill, Ellen Bernadette. "A mathematical liver model and its application to system optimization and texture analysis". Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184936.
Texto completoEaston, Jonathan. "Mathematical models of health focusing on diabetes : delay differential equations and data mining". Thesis, Northumbria University, 2015. http://nrl.northumbria.ac.uk/23582/.
Texto completoVogel, Vance T. "Determining personnel accession requirements for Medical Service Corps Health Care Administrators using a steady state analysis /". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FVogel.pdf.
Texto completoThesis Advisor(s): Anke Richter, Kathryn M. Kocher. Includes bibliographical references (p. 113-114 ). Also available online.
Al-otoum, Mohammed Fawzi. "Evaluation of bootstrapping as a validation technique for population pharmacokinetic models". Scholarly Commons, 2004. https://scholarlycommons.pacific.edu/uop_etds/590.
Texto completoSimoni, Giulia. "Modeling Startegies for Computational Systems Biology". Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254361.
Texto completoYORIYAZ, HELIO. "Desenvolvimento de uma metodologia computacional para calculos em dosimetria interna". reponame:Repositório Institucional do IPEN, 2000. http://repositorio.ipen.br:8080/xmlui/handle/123456789/10791.
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Tese (Doutoramento)
IPEN/T
Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP
Pozdin, Maksym O. "Automated Extraction of Subdural Grid Electrodes from Post-Implant MRI Scans for Epilepsy Surgery". Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4979.
Texto completoMajeke, Lunga. "Preliminary investigation into estimating eye disease incidence rate from age specific prevalence data". Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/464.
Texto completoMannan, Haider Rashid. "Development and use of a Monte Carlo-Markov cycle tree model for coronary heart disease incidence-mortality and health service usage with explicit recognition of coronary artery revascularization procedures (CARPs)". University of Western Australia. School of Population Health, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0101.
Texto completoMukhtar, Abdulaziz Y. A. "Mathematical modeling of population dynamics of HIV with antiretroviral treatment and herbal medicine". Thesis, University of Western Cape, 2014. http://hdl.handle.net/11394/3351.
Texto completoHerbal medicines have been an important part of health and wellness for hundreds of years. Recently the World Health Organization estimated that 80% of people worldwide rely on herbal medicines. Herbs contain many substances that are good for protecting the body and are therefore used in the treatment of various illnesses. Along with traditional medicines, herbs are often used in the treatment of chronic diseases such as rheumatism, migraine, chronic fatigue, asthma, eczema, and irritable bowel syndrome, among others. Herbal medicines are also applied in certain traditional communities as treatment against infectious diseases such as flu, malaria, measles, and even human immunodeficiency virus HIV-infection. Approximately 34 million people are currently infected with the human immunodeficiency virus (HIV) and 2.5 million newly infected. Therefore, HIV has become one of the major public health problems worldwide. It is important to understand the impact of herbal medicines used on HIV/AIDS. Mathematical models enable us to make predictions about the qualitative behaviour of disease outbreaks and evaluation of the impact of prevention or intervention strategies. In this dissertation we explore mathematical models for studying the effect of usage of herbal medicines on HIV. In particular we analyze a mathematical model for population dynamics of HIV/AIDS. The latter will include the impact of herbal medicines and traditional healing methods. The HIV model exhibits two steady states; a trivial steady state (HIV-infection free population) and a non-trivial steady state (persistence of HIV infection). We investigate the local asymptotic stability of the deterministic epidemic model and similar properties in terms of the basic reproduction number. Furthermore, we investigate for optimal control strategies. We study a stochastic version of the deterministic model by introducing white noise and show that this model has a unique global positive solution. We also study computationally the stochastic stability of the white noise perturbation model. Finally, qualitative results are illustrated by means of numerical simulations. Some articles from the literature that feature prominently in this dissertation are [14] of Cai et al, [10] of Bhunu et al., [86] of Van den Driessche and Watmough, [64] of Naresh et al., Through the study in this dissertation, we have prepared a research paper [1], jointly with the supervisors to be submitted for publication in an accredited journal. The author of this dissertation also contributed to the research paper [2], which close to completion. 1. Abdulaziz Y.A. Mukhtar, Peter J. Witbooi and Gail D. Hughes. A mathematical model for population dynamics of HIV with ARV and herbal medicine. 2. P.J. Witbooi, T. Seatlhodi, A.Y.A. Mukhtar, E. Mwambene. Mathematical modeling of HIV/AIDS with recruitment of infecteds.
Johnson, Kevin Robert. "In Vivo Coronary Wall Shear Stress Determination Using CT, MRI, and Computational Fluid Dynamics". Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14482.
Texto completoHarbord, Ruth. "Time-varying brain connectivity with multiregression dynamic models". Thesis, University of Warwick, 2017. http://wrap.warwick.ac.uk/101426/.
Texto completoWilliams, John. "A mathematical model of the dynamics of hepatitis B virus transmission in the UK under the influence of different vaccination control strategies". Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298721.
Texto completoChin, Sze Vone. "Structural identifiability and indistinguishability analyses of glucose-insulin models". Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/38108/.
Texto completoFord, Ashley P. "Epidemic models and MCMC inference". Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66495/.
Texto completoLima, Ernesto Augusto Bueno da Fonseca. "Phase-field models of tumor growth with angiogenesis". Laboratório Nacional de Computação Científica, 2014. https://tede.lncc.br/handle/tede/180.
Texto completoConselho Nacional de Desenvolvimento Cientifico e Tecnologico
The development of predictive computational models of tumor initiation, growth, and decline is faced with many formidable challenges. Phenomenological models which attempt to capture the complex interactions of multiple tissue and cellular species must cope with moving interfaces of heterogeneous media and the huge uncertainties of the parameters and their evolution. They must be able to deliver predictions consistent with events that take place at cellular scales, and they must faithfully depict biological mechanisms and events that are known to be associated with various forms of cancer. In the present work, some models for the tumor behavior are presented which fall within the framework of phase-field (or diffuse-interface) models suggested by continuum mixture theory. This framework provides for the simultaneous treatment of interactions of multiple evolving species, such as tumor cells, necrotic cell cores, nutrients, and other cellular and tissue types that exist and interact in living tissue. In the present work, a hybrid phase field ten-species vascular model for the tumor growth is developed, which couples the tumor growth with sprouting through angiogenesis. The model is able to represent the branching of new vessels through coupling a discrete model for which the angiogenesis is started upon pre-defined conditions on the nutrient deprivation in the continuum model. Such conditions are represented by hypoxic cells that release tumor growth factors that ultimately trigger vascular growth. We discuss the numerical approximation of the model using mixed finite elements. We also consider an avascular stochastic six-species tumor growth model derived directly from the hybrid ten-species model. The stochasticity comes from modeling uncertainties in the parameters of the model. We perform a sensitivity analysis to identify the more relevant parameters on the tumor mass growth. The stochastic model is then developed taking into account the uncertainty of the most influential parameter. The numerical approximation of the model using Stochastic Collocation method to treat uncertainties in the nonlinear system is presented. The results of numerous numerical experiments are also presented and discussed.
Modelos matematicos e computacionais sao utilizados na compreensao de fenomenos complexos, sendo aplicados em diversas areas como engenharia, fisica e biologia. Na Medicina tem um importante papel na simulacao do tratamento e evolucao de algumas doencas, entre elas o cancer. O desenvolvimento de modelos computacionais para o crescimento tumoral se depara com desafios formidaveis. Modelos fenomenologicos que tentam capturar as complexas interacoes de multiplos tecidos e especies celulares devem lidar com interfaces em meios heterogeneos e as enormes incertezas dos parametros e suas evolucoes. Eles devem ser capazes de proporcionar predicoes consistentes com eventos que ocorrem em escalas celulares, e devem representar fielmente os mecanismos biologicos associados ao cancer. No presente trabalho, sao apresentados alguns modelos para o crescimento tumoral. Esses modelos inserem-se no ambito de modelos de campo de fase (ou interface difusiva) sugeridos pela teoria mistura. Esta metodologia preve o tratamento simultaneo de interacoes entre multiplos constituintes, como as celulas tumorais, celulas necroticas, nutrientes e outros tipos celulares e teciduais que existem e interagem em tecidos vivos. Neste trabalho, um modelo hibrido de campo de fases, de dez constituintes e desenvolvido para o crescimento tumoral vascular, que acopla o crescimento de tumores com crescimento de novos vasos sanguineos atraves da angiogenese. O modelo é capaz de representar a ramificacao de novos vasos atraves do acoplamento de um modelo discreto, no qual a angiogenese é iniciada mediante condicoes pre-definidas, relacionadas a privacao de nutrientes no modelo macroscopico. Tais condicoes sao representadas por celulas hipoxicas que liberam quimicos reponsaveis por induzir a angiogenese tumoral. A aproximacao numerica do modelo usando elementos finitos mistos é discutida. Considera-se tambem um modelo estocastico avascular de seis constituintes para o crescimento tumoral, derivado diretamente do modelo hibrido de dez constituintes. A estocasticidade vem de incertezas na modelagem dos parametros do modelo. Realiza-se uma analise de sensibilidade para identificar os parametros mais relevantes sobre o crescimento da massa tumoral. O modelo estocastico é entao desenvolvido tendo em conta a incerteza no parametro mais influente. A aproximacao numerica do modelo usando o metodo estocastico de Colocacao para tratar incertezas no sistema nao-linear é apresentada. Os resultados de varios experimentos numericos tambem sao apresentados e discutidos.
Griffin, Adam. "Quasi-stationary distributions for evolving epidemic models : simulation and characterisation". Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/89671/.
Texto completoBarons, Martine J. "What is the added value of using non-linear models to explore complex healthcare datasets?" Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/58401/.
Texto completoCharoenphon, Sutthirut. "Green's Functions of Discrete Fractional Calculus Boundary Value Problems and an Application of Discrete Fractional Calculus to a Pharmacokinetic Model". TopSCHOLAR®, 2014. http://digitalcommons.wku.edu/theses/1327.
Texto completoGanjgahi, Habib. "Computationally efficient mixed effect model for genetic analysis of high dimensional neuroimaging data". Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/91328/.
Texto completoOrtega, Neli Regina de Siqueira. "Aplicação da teoria de conjuntos Fuzzy a problemas da biomedicina". Universidade de São Paulo, 2001. http://www.teses.usp.br/teses/disponiveis/43/43134/tde-04122013-133237/.
Texto completoBiological, medical and epidemic systems present several types of inherent uncertainties to its processes. Many of these uncertainties have been treated in an efficient way with statistical and Bayesian models. Though, these areas still lack of mathematical structures that make possible the treatment of the non-statistical uncertainties typical of some of these systems. Besides, the use of linguistic terms to express quantitatively the variables is very common in these areas. So, due to its features, the fuzzy logic comes as an appropriate theory to treat some of these problems. The aim of this thesis was to develop applications of the fuzzy logic theory to problems of biomedicine. Our challenge was to propose paths, to look for ways, of accomplishing an effective junction off this theory with the mentioned areas, mainly with epidemiology. Eight works were elaborated, where several aspects of this theory were approached, such as: static and dynamic fuzzy linguistic models, fuzzy decision making, probability of fuzzy events, fuzzy relations and the use of extension principle in the construction of fuzzy rules. We conclude that the fuzzy logic theory can aid in the treatment of many epidemiological problems, as well as diagnostic systems. We also show that it can work effectively in decision making processes of Public Health. Some systems can, pottentially, help the physicians in the diagnosis and prognostic of diseases, mainly in the specialists absence. The static linguistic models worked well, however, difficulties concerning the dynamic models still need to be overcome. We also discuss the specialists role in the elaboration of fuzzy models in epidemiology and propose a method for elaboration of less dependent models. All the works presented good results, stimulating the continuity of the researches in this area.
Wang, Lipeng. "THE ROLE OF ABCG2 IN DRUG ACTIVE TRANSPORT IN MILK". UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_diss/59.
Texto completoRocha, Heber Lima da. "Modelagem híbrida multiescala para o crescimento tumoral". Laboratório Nacional de Computação Científica, 2016. https://tede.lncc.br/handle/tede/236.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Cancer is a huge world health problem, what is expanding researches on a wide variety of subjects associated with its onset, evolution and treatment. In this work, we perfom a detailed study on the tumor growth mechanisms in order to build a model to describe the evolution of tumors at different scales. We develop a multiscale hybrid model for the avascular tumor growth which integrates phenomena that occur at two scales, the cellular and tissue scales. The cellular scale is described through an agent based model, allowing to deal with each cell individually and to describe the cell behavior in the microenvironment. We represent the nutrient transport in the microenvironment at the tissue scale through a reaction-diffusion partial differential equation. The oxygen is considered the only source of nutrients and its uptake rate plays the role of the bridge between scales. The model encompasses tumor and normal cells, but the latter are kept in homeostasis. Phenotypic states differentiate tumor cells (quiescent, proliferative, apoptotic, hypoxic and necrotic), which may change in accordance with microenvironment conditions. The tumor growth dynamics is ruled by phenotypic transitions, which are mainly deterministic. However, the transitions from quiescent to proliferative and apoptotic states are stochastic. Each cell movement is driven by the force balance among cells, according to Newton's second law. By including normal cells, the tumor growth strongly depends on the mechanical interactions in the microenvironment. To describe these effects, we develop a model to represent the compressive stress accumulation within the growing tumor, which acts by inhibiting further cell proliferation. Computational simulations are conducted to demonstrate that the developed model can adequately describe the complex mechanisms of tumor dynamics, including growth arrest in avascular tumors.
O câncer é um enorme problema de saúde global, o que vem impulsionando pesquisas nas mais diversas áreas associadas ao seu surgimento, evolução e terapias. Neste trabalho realizamos um estudo minucioso acerca do crescimento tumoral a fim de construir um modelo que descreve o crescimento tumoral em diversas escalas. Desenvolvemos um modelo multiescala híbrido para o crescimento tumoral avascular que integra fenômenos que ocorrem em duas escalas, uma escala a nível celular e outra a nível de tecido. A escala celular é descrita através de um modelo baseado em agentes, que possibilita tratar cada célula individualmente e descrever seu comportamento no microambiente. Na escala do tecido representamos a dispersão de nutrientes no meio através de uma equação diferencial parcial de reação-difusão. Consideramos o oxigênio como a única fonte de nutrientes e seu consumo é o mecanismo através do qual o acoplamento entre as escalas é realizado. Consideramos que cada célula no modelo pode ser tumoral ou normal, sendo as células normais mantidas em homeostase. As células tumorais são diferenciadas pelos estados fenotípicos (quiescente, proliferativa, apoptótica, hipóxica e necrótica), que podem ser alterados em função das condições do meio. A dinâmica do crescimento tumoral é regida pelas transições entre estados fenotípicos, as quais, em sua maioria, são consideradas eventos determinísticos. Entretanto, as transições do estado quiescente para o proliferativo e para o apoptótico são assumidas como estocásticas. O movimento de cada célula no meio é determinado por um balanço de forças atuantes nas células, de acordo com a segunda lei de Newton. Com a inclusão de células normais, o crescimento do tumor é fortemente influenciado pelas interações mecânicas no microambiente. Para descrever estes efeitos, desenvolvemos um modelo para representar o acúmulo das tensões de compressão no interior do tumor à medida que o tumor cresce, o qual atua inibindo a probabilidade de proliferação das células tumorais. As simulações realizadas demonstram que o modelo desenvolvido consegue representar qualitativamente a dinâmica de tumores em um microambiente genérico e a estagnação do crescimento típica de tumores avasculares.
Resende, Anna Claudia Mello de. "Sensitivity analysis as a tool for tumor growth modeling". Laboratório Nacional de Computação Científica, 2016. https://tede.lncc.br/handle/tede/237.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Mathematical and computational modeling of tumor growth have become valuable tools for learning and understanding various aspects of tumor onset and development. They can also help to generate new hypotheses for experimental testing and to verify the efficiency or optimize clinical therapies. From the computational point of view, a huge challenge is to deal with highly nonlinear and multi-components mathematical models that aim to display multiple types of biological interactions across different biological, temporal and physical scales. Computational and numerical difficulties usually appear. Also, nonlinear interactions may give rise to interesting and unexpected dynamics which make it difficult to anticipate a model's outcome. Here we make a step towards developing a model-building framework to improve the understanding of the model itself and the key issues to drive model modifications and simplifications. We develop a family of deterministic tumor growth models based on a mathematical model built in the literature, which is a continuous model of seven coupled nonlinear partial differential equations that can capture both avascular and vascular phases of the disease. Although simple, this model provides considerable insight about important mechanisms related to tumor progression, as angiogenesis, for example, which is the fundamental strategy tumors acquire to keep and improve growth. Its main assumptions and mathematical formulation are discussed in details, and we propose some modifications to fix ambiguities in the original model. The extension to multidimensional problems is considered, for which we develop reliable approximate finite element solution. We propose in this work a simple framework to build a hierarchical family of tumor growth models by selecting a subset of the most important parameters of our base model with respect to the evolution of the tumor volume. The importance of each parameter is identified through two model-free sensitivity analysis techniques, the construction of scatterplots and the elementary effects, due to their simplicity and low computational costs. This model framework encompasses the essential hypotheses and the limited set of important parameters acquired from the sensitivity analysis. In this way, we are able to create a family of models described by at least the same essential conditions and parameters but with different complexities regarding the number of parameters used. Numerical experiments are conducted to provide a comprehensive understanding of the hierarchical developed family of tumor growth models. Finally, we emphasize that the modeling framework in this manner provides a powerful way for studying a model itself or either its simplification or extension. The framework can also be tailored to form the basis for future models, incorporating new processes and phenomena.
A modelagem matemática e computacional do crescimento tumoral tornou-se uma ferramenta importante para o aprendizado e entendimento de vários aspectos relacionados ao surgimento e desenvolvimento de tumores. Esta ferramenta é também capaz de ajudar a construir novas hipóteses para testes experimentais, verificar a eficiência e até mesmo otimizar terapias. Do ponto de vista computacional, um grande desafio consiste em resolver e entender modelos matemáticos não-lineares com múltiplos componentes que objetivam representar interações que ocorrem em diferentes escalas biológicas, de tempo e espaço. Dificuldades numéricas e computacionais ocorrem frequentemente. Interações não-lineares dão também origem a dinâmicas interessantes e até mesmo inesperadas, dificultando antecipar os resultados de muitos modelos. Neste trabalho, dá-se um passo na direção do desenvolvimento de uma abordagem para a construção de modelos que permite tornar mais claro o entendimento destes e de seus aspectos-chave, auxiliando modificações e simplificações para tornar o processo de modelagem mais simples. Desenvolvemos uma família de modelos determinísticos para o crescimento tumoral baseada em um modelo não-linear e contínuo apresentado na literatura que contém sete equações diferenciais parciais acopladas, capaz de capturar as fases avascular e vascular da doença. Embora simples, este modelo proporciona o entendimento dos importantes mecanismos relacionados à progressão de tumores, como a angiogênese, por exemplo, que é a estratégia utilizada por um tumor para manter e impulsionar seu crescimento. As principais hipóteses e formulação matemática deste modelo-base são discutidas em detalhes, e algumas modificações são propostas para corrigir ambiguidades presentes no modelo original. A extensão para problemas multidimensionais é considerada, para a qual desenvolvemos uma solução robusta de elementos finitos. Neste trabalho, propomos uma abordagem simples para a construção de uma família hierárquica de modelos de crescimento tumoral através da seleção do conjunto de parâmetros mais importantes de um modelo-base com respeito à evolução do volume tumoral. A importância de cada parâmetro é identificada através de duas técnicas de análise de sensibilidade consideradas simples, de baixo custo computacional e independentes do modelo utilizado: a construção de scatterplots e efeitos elementares. A abordagem de modelagem inclui as hipóteses essenciais e um conjunto limitado de parâmetros identificados como importantes na análise de sensibilidade. Deste modo, é possível criar uma família de modelos descrita no mínimo pelas mesmas condições essenciais e parâmetros importantes, mas com diferentes complexidades com relação ao número de parâmetros utilizados na modelagem. Experimentos numéricos são realizados para promover o entendimento sobre a família hierárquica de modelos desenvolvida. Finalmente, enfatizamos que a abordagem de modelagem desenvolvida desta maneira proporciona um potencial mecanismo para estudar um modelo e suas simplificações e extensões. Esta abordagem pode ser ajustada para formar a base para modelos futuros, incorporando novos processos e fenômenos.
Oyero, Oyebola E. "Comparison of Two Methods for Developing Aggregate Population-Based Models". Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3139.
Texto completoDeschamps, Thomas. "Extraction de Courbes et Surfaces par Methodes de Chemins Minimaux et Ensembles de Niveaux. Applications en Imagerie Medicale 3D". Phd thesis, Université Paris Dauphine - Paris IX, 2001. http://tel.archives-ouvertes.fr/tel-00003335.
Texto completoPadmanabhan, Kiran. "Modified alginates as a matrix for gene transfection in a HeLa cell model". Scholarly Commons, 2000. https://scholarlycommons.pacific.edu/uop_etds/547.
Texto completoSun, Jingjing. "Exploring the effect of alpha2 receptor on brain 5-HT via a mechanism-based pharmacodynamic model". Scholarly Commons, 2012. https://scholarlycommons.pacific.edu/uop_etds/154.
Texto completoSéqueira, Jean. "Modélisation interactive d'objets de forme complexe à partir de données hétérogènes : application à la représentation géométrique des organes du corps humain". Besançon, 1987. http://www.theses.fr/1987BESA2028.
Texto completoJackson, Arthur Rhydon. "Predicting Flavonoid UGT Regioselectivity with Graphical Residue Models and Machine Learning". Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etd/1820.
Texto completoAkcin, Haci Mustafa. "Direct adjustment method on Aalen's additive hazards model for competing risks data". unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-04182008-095207/.
Texto completoTitle from file title page. Xu Zhang, committee chair; Yichuan Zhao, Jiawei Liu, Yu-Sheng Hsu, committee members. Electronic text (51 p.) : digital, PDF file. Description based on contents viewed July 15, 2008. Includes bibliographical references (p. 50-51).
Vangala, Swathi. "Human Cytochrome P450 3A4 Over-Expressing IEC-18 and MDCK Cell Lines as an In-Vitro Model to Assess Gut Permeability and the Enzyme Metabolism". Scholarly Commons, 2013. https://scholarlycommons.pacific.edu/uop_etds/273.
Texto completoPadmanabhan, Kiran. "Modified alginates as a matrix for gene transfection in a HeLa cell model : a thesis". Scholarly Commons, 2001. https://scholarlycommons.pacific.edu/uop_etds/547.
Texto completoSantos, Fabiano de Sant'ana dos. "Incidência de infecções virais das vias aeríferas superiores em crianças e seu estudo por meio de um modelo matemático". Faculdade de Medicina de São José do Rio Preto, 2009. http://bdtd.famerp.br/handle/tede/58.
Texto completoAcute respiratory infections, especially upper respiratory tract infections (URTI), are the most frequent causes of infantile morbidity in the world. Day-care facilities are closed, with great circulation of people and infectious agents as well, being therefore prone to the spreading of viral respiratory infections. Mathematical epidemic models are quantitative analysis methods that might be used for understanding and predicting the transmission dynamics of infectious diseases. Objective: Verify the monthly incidence of URTI, of 8 respiratory viruses, and to simulate a mathematical model, evaluating its qualitative and quantitative behavior regarding true data from URTI in school of infantile education in integral period children. Casuistic and Methods: From July 2003 to July 2004, all children (173) in the school of infantile education in integral period were followed from 1.6 to 12 months. Them presenting signs of respiratory infections were examined and their nasopharyngeal aspirate specimen was collected, in a total of 255 analyses. Soon after, specific multiplex trial of reverse transcription, followed by the polymerase chain reaction (multiplex RT-PCR), was accomplished for identification of the 8 viruses related to respiratory infections. Results and Conclusions: The average incidence of URTI was 2.33 episodes per child-year. URTI was observed throughout the year of study, especially in the fall and winter, lowering during spring and presenting few cases in summer. Rhinovirus presented the greatest incidence, being observed throughout the period of study. Influenza B, respiratory syncytial virus (RSV), and metapneumovirus presented lower incidence, especially during fall and winter. URTI caused by other analyzed viruses - influenza A, parainfluenza 1, 2, and 3 were rare. The evaluation of the mathematical model through simulations has provided promising results, as it was possible to get true data reproduction. The model is promising. Having its suppositions adequate, it might be useful for understanding the dynamics and spreading of diseases, planning and evaluating prevention and immunization strategies in epidemics.
As infecções respiratórias agudas, em especial as infecções das vias aeríferas superiores (IVAS), são as causas mais freqüentes de morbidade infantil no mundo. As creches são ambientes fechados, onde há grande circulação de pessoas e também de agentes infecciosos, sendo então favoráveis à disseminação de infecções respiratórias virais. Os modelos epidemiológicos matemáticos são métodos de análise quantitativos e podem ser usados para compreensão e predição da dinâmica de transmissão de uma doença infecciosa. Objetivo: Verificar a incidência mensal de IVAS, de 8 vírus respiratórios, e simular um modelo matemático, avaliando seu comportamento qualitativo e quantitativo em relação aos dados reais de IVAS nas crianças da Escola de Educação Infantil em período integral. Casuística e Método: Todas as crianças (173) que freqüentaram a escola no período de julho de 2003 a julho de 2004 foram acompanhadas por 1,6 a 12 meses. Elas apresentaram sinais de IVAS foram examinadas e tiveram coletado espécime de aspirado de nasofaringe, perfazendo um total de 255 análises. Em seguida, foi realizado ensaio específico multiplex de transcrição reversa seguida da reação em cadeia de polimerase (multiplex RT-PCR) para identificação dos 8 vírus relacionados às IVAS. Resultados e Conclusões: A incidência média de IVAS foi de 2,33 episódios por criança-ano. As IVAS incidiram durante todo o período do estudo, principalmente no outono e inverno, decaindo na primavera e com poucos casos no verão. O rinovírus teve maior incidência tendo sido observado em todos os períodos em que ocorreram episódios de IVAS. Influenza B, vírus sincicial respiratório (VSR) e metapneumovírus ocorreram com menor incidência, principalmente no outono e inverno. IVAS causadas pelos outros vírus analisados influenza A, parainfluenza 1, 2 e 3 foram raras. A avaliação do modelo matemático, por meio de simulações, forneceu resultados animadores, visto que se conseguiu a reprodução dos dados reais. O modelo é promissor. Com a adequação das suas suposições, pode ser útil para a compreensão das dinâmicas de disseminação de doenças, planejamento e avaliação de estratégias de prevenção e de imunização em epidemias.
Olofsson, Nils. "Kidney Dynamic Model Enrichment". Thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242315.
Texto completoFraga, Keith Jeffrey. "Explorations into protein structure with the knob-socket model". Scholarly Commons, 2016. https://scholarlycommons.pacific.edu/uop_etds/264.
Texto completoZhou, Zhu. "Exploring the effects of 5-HT2A and AMPA receptors on brain 5-HT via a mechanism-based pharmacodynamic model". Scholarly Commons, 2014. https://scholarlycommons.pacific.edu/uop_etds/143.
Texto completoZhao, Xiaoning. "Synthesis and applications of functional magnetic polymer beads; synthesis and mass spectrometry analysis of model peptides". Scholarly Commons, 2012. https://scholarlycommons.pacific.edu/uop_etds/156.
Texto completoDong, Jin. "First-principle based pharmacokinetic modeling". Scholarly Commons, 2016. https://scholarlycommons.pacific.edu/uop_etds/128.
Texto completoChada, Kinnera. "COMPUTATIONAL ANALYSES OF THE UPTAKE AND DISTRIBUTION OF CARBON MONOXIDE (CO) IN HUMAN SUBJECTS". UKnowledge, 2011. http://uknowledge.uky.edu/gradschool_diss/224.
Texto completoZhang, Changfeng. "Investigation of the endoplsmic reticulum calcium stores for their potential roles in neuroprotection using the NG115-401L neuronal cell line model". Scholarly Commons, 2014. https://scholarlycommons.pacific.edu/uop_etds/142.
Texto completoLaghetto, Beatriz Krabbe. "Um modelo matemático para estimar o risco de desenvolver câncer de pulmão por meio de sistemas fuzzy". Universidade Federal de São Carlos, 2016. https://repositorio.ufscar.br/handle/ufscar/8040.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
The main aims of this work are to study the ways to model mathematically uncertainties using Fuzzy Sets Theory, and then propose a mathematical model to estimate the risk of an individual developing lung cancer through a system based rule fuzzy. Therefore, we consider risk factors, namely smoking, pollution, history of lung disease, family history and contact with chemical agents such as system input variables fuzzy. Lung cancer is a disease that has no symptoms in its early stages, making the diagnosis more difficult to be done and, therefore, most discovered when the cancer is already advanced. This type of cancer is highly lethal and frequent in the population, an increase of 2 % per year in its worldwide incidence.
Os principais objetivos desse trabalho são estudar as formas de modelar matematicamente certas incertezas por meio da Teoria dos Conjuntos Fuzzy e, em seguida, propor um modelo matemático para estimar o risco de um indivíduo desenvolver câncer de pulmão por meio um sistema baseado em regras fuzzy. Para isso, consideramos fatores de risco, tais como, tabagismo, poluição, histórico de doenças pulmonares, histórico familiar e contato com agentes químicos como variáveis de entrada do sistema fuzzy. O câncer de pulmão é uma doença que não apresenta sintomas em suas fases iniciais, tornando o diagnóstico mais difícil de ser feito e, por isso, a maioria descobre quando o câncer já está avançado. Esse tipo de câncer é altamente letal e frequente na população, apresentando aumento de 2% ao ano na sua incidência mundial.
Pax, Benjamin M. "Prediction of Bronchopulmonary Dysplasia by a Priori and Longitudinal Risk Factors in Extremely Premature Infants". Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1522686042230784.
Texto completoSu, Dan. "Rational design, characterization and in vivo studies of antibody mimics against HER2". Scholarly Commons, 2015. https://scholarlycommons.pacific.edu/uop_etds/133.
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