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Padrões de atividade física e proteína C reativa no estudo longitudinal de saúde do adulto (ELSA-Brasil)Queiroz, Ciro Oliveira January 2013 (has links)
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Previous issue date: 2013 / Fundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Salvador, BA, Brasil / Introdução: A proteína C reativa (PCR) é um biomarcador conhecido da
inflamação sistêmica e está associado à predição de doenças cardiovasculares. A
atividade física regular tem muitos benefícios, uma vez que reduz o risco do
desenvolvimento de diversas doenças crônicas, incluindo as doenças
cardiovasculares. Alguns estudos tem mostrado que a atividade física pode estar
inversamente associada aos níveis de PCR, entretanto, ainda não se tem um
consenso sobre a quantidade de atividade física necessária para manter os níveis
de PCR normais. Objetivo: identificar o poder discriminatório e a quantidade de
atividade física necessária para discriminar níveis de PCR em adultos. Métodos:
estudo transversal com amostra de 14.250 adultos de 35 a 74 anos de idade,
participantes do Estudo Longitudinal de Saúde do Adulto. Foram construídas
curvas Receiver Operating Characteristic (ROC) para identificar o poder preditivo
e os pontos de corte da quantidade de atividade física em dois domínios (tempo
livre e deslocamento) e níveis de PCR. Para testar as diferenças entre as áreas
sob a curva ROC utilizou-se o teste qui-quadrado considerando-se 5% de nível de
significância estatística. Verificou-se a sensibilidade e especificidade para
identificar os melhores pontos de corte de atividade física necessários para
manter níveis normais de PCR (<3mg/L). Resultados: a maior parte dos
participantes tem nível superior completo (53,1%), são da cor branca (52,4%) e
tem sobrepeso (40,7%). Com relação a PCR, um quarto da amostra se encontra
com níveis elevados (25,2%) e quando comparado por sexo, as mulheres
apresentam uma maior proporção. Quando se avaliou a quantidade de atividade
física realizada por semana, 57,5% dos participantes do estudo não praticavam
no mínimo 10 minutos de atividade física no tempo livre. Encontrou-se
significância estatística das áreas sob a curva ROC na soma dos dois domínios
investigados e no domínio do tempo livre isoladamente. A atividade física
acumulada nos dois domínios durante 200 minutos/semana apresentou o melhor
equilíbrio para discriminar os níveis normais de PCR em adultos de ambos os
sexos. Conclusão: a prática de atividade física combinada nos domínios do tempo
livre e deslocamento podem contribuir para manter os níveis de PCR normais.
Esses achados podem contribuir também para a construção de políticas públicas
em relação à promoção da atividade física e da saúde. / Background: C-reactive protein (CRP) is a known biomarker of systemic
inflammation and is associated with the prediction of cardiovascular disease.
Regular physical activity has many benefits, as it reduces the risk of developing
several chronic diseases, including cardiovascular disease. Some studies have
shown that physical activity may be inversely associated with levels of CRP,
however, there isn’t still consensus on the amount of physical activity required to
maintain levels of CRP normal. Purpose: Identify the discriminatory power and
amount of physical activity required to discriminate levels of CRP in adults.
Methods: Cross-sectional study with a sample of 14.250 adults age 35 to 74 years,
participating in the Brazilian Longitudinal Study of Adult Health. Receiver
Operating Characteristic (ROC) curves was constructed to identify the predictive
power and the cutoff of physical activity in two domains (leisure time and
displacement) and levels of CRP. To test the differences between the areas under
the ROC curve was used the chi-square test considering a 5% significance level.
Sensitivity and specificity were observed to identify the best cut-off of physical
activity to keep normal levels CRP (<3mg/L). Results: The most participants have
completed college (53.1%) are white (52.4%) and is overweight (40.7%). With
respect to CRP, a quarter of participants meets high levels (25.2%) and compared
by sex, women have a higher proportion. When assessing the amount of physical
activity per week, 57.5% of study participants did not practice at least 10 minutes
of physical activity during leisure time It was found a statistical significance of the
areas under the ROC curve of the sum of the two domains investigated and in the
leisure time alone. Physical activity accumulated in the two domains during 200
minutes/week showed the best balance for discriminating normal levels of CRP in
adults of both sexes. Conclusion: The physical activity combined in the domains of
leisure time and displacement may contribute to keep the levels of CRP normal.
These findings may also contribute to the development of public policies regarding
promotion of physical activity and health.
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Método para avaliação dos algoritmos utilizados no processamento de imagens médicas / Method for evaluation of the algorithms used in the processing of medical imagesSilvia Cristina Martini Rodrigues 24 September 1999 (has links)
Este trabalho apresenta como parte de resultados, uma ampla pesquisa que permitiu identificar os grupos de pesquisas mais importantes do mundo, os quais possuem em comum o processamento de imagens médicas, mais especificamente o processamento de imagens que busca a identificação de microcalcificações mamárias. O vasto levantamento, a seleção e organização culminou na reunião de mais de cem artigos, publicados nos mais importantes periódicos da área, que mostram claramente as formas utilizadas pelos grupos de pesquisa para apresentação dos resultados encontrados pelos seus algoritmos. Esses resultados devem auxiliar o médico no diagnóstico do câncer de mama. Demonstramos neste trabalho porque as técnicas utilizadas para apresentação dos resultados são insatisfatórias e propusemos um novo método de avaliação desses resultados. O método proposto no trabalho baseia-se no teste do X² (Qui-Quadrado), nas curvas ROC (Receiver Operating Characteristic) e no teste de concordância, que juntos permitem apresentar de forma clara e objetiva as relações entre verdadeiros positivos e falsos positivos, verdadeiros negativos e falsos negativos, sensibilidade e especificidade do algoritmo analisado. O novo método é preciso e tem bases estatísticas conhecidas pelos médicos e pelos pesquisadores, facilitando sua aceitação. / This work presents as part of results, a wide investigation that it allowed to identify the principal research groups of the world, which possess in common the processing of medical images, more specifically the processing of images that search for the identification of mammary microcalcifications. The vast collection, selection and organization culminated in the meeting of more than a hundred articles, published in the most important newspapers of the area, that show the forms used by the research groups to present the results found clearly by its algorithms. Those results should assist the doctor in the diagnosis of the breast cancer. We demonstrated in this work that the techniques used for presentation of the results are unsatisfactory and we proposed a new method of evaluation of those results. The proposed method bases on the test of the X² (Qui-square), in ROC curve (Receiver Operating Characteristic) and in the agreement test, that take together allow to present in a clear and objective way the relationships among true positive and false positive, true negative and false negative, sensibility and specificity of the analyzed algorithm. The new method is precise and has statistical bases known by the clinicians and researchers, facilitating its acceptance.
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Influência de diferentes tempos de exposição na detecção de cárie em um sistema digital wireless / Effect of different exposure times on caries detection using a wireless digital systemMelo, Daniela Pita de 17 August 2018 (has links)
Orientador: Paulo Sérgio Flores Campos / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba / Made available in DSpace on 2018-08-17T13:43:28Z (GMT). No. of bitstreams: 1
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Previous issue date: 2010 / Resumo: O objetivo, neste trabalho, foi verificar se diferentes tempos de exposição interferem no diagnóstico de cáries proximais e no valor médio do pixel da imagem do sistema Schick CDR Wireless. Foram obtidas imagens de 10 phantoms, constituídos de dentes humanos, e de uma escala de alumínio
utilizando-se diferentes tempos de exposição. Os oito tempos de exposição estudados foram em ordem crescente: 0,06s, 0,1s, 0,13s, 0,16s, 0,2s, 0,25s, 0,3s e 0,35s. As imagens dos phantoms obtidas com os tempos selecionados foram interpretadas por quatro avaliadores quanto à presença de cárie proximal. Cada avaliador atribuiu um escore para cada uma das faces dentárias interpretadas. Esses escores foram posteriormente comparados aos cortes histológicos. Os tempos de exposição foram avaliados, quanto à sua acurácia no diagnóstico de cárie, por meio da curva ROC. As imagens obtidas da escala de Al em diferentes tempos de exposição tiveram o valor médio do pixel mensurado utilizando-se a ferramenta apropriada do software EMAGO®/Advanced. As médias das curvas ROC correspondentes aos tempos de exposição avaliados variaram de 0,53 a 0,62, sendo que a faixa de tempos que apresentou melhor resultado variou de 0,06s a 0,25s; destes, o tempo 0,25s obteve o melhor resultado. Quanto ao valor médio do pixel, foram observados dois comportamentos distintos nos tempos estudados, entretanto, o tempo de 0,20s apresentou valor médio do pixel nas duas fases comportamentais. O desempenho dos tempos de exposição entre 0,06s e 0,25s foi satisfatório no diagnóstico de cáries proximais, sendo o tempo 0,25s o mais indicado para essa finalidade / Abstract: The aim on this study was to evaluate the influence of different exposure times on proximal caries detection and on mean pixel values of the Schick CDR Wireless digital image. Ten human teeth phantoms and an aluminum scale were radiographed using different exposure times. The eight studied exposure times were: 0.06s, 0.1s, 0.13s, 0.16s, 0.2s, 0.25s, 0.3s and 0.35s.The images of them phantoms in different exposure times were evaluated by four observers for the presence of caries lesions. Each observer scored the proximal surfaces of each tooth. The scores were compared to the golden standard. The exposure times were evaluated on their accuracy of predicting caries by means of the ROC curve analysis. The images of the aluminum scale using different exposure times had their mean pixel values measured using the appropriate tool of the EMAGO®/Advanced software. The means of the ROC curves of each exposure time evaluated varied from 0.53 to 0.62, and the exposure time range between 0.06s to 0.25s presented better results, and the exposure time of 0.25s presented the highest Az from them. In regard to mean pixel values, two different behaviors were observed, and the exposure time of 0,20s presented mean pixels values in the two behavior phases. The behavior of the exposure times from 0.06s to 0.25s was satisfactory for proximal caries detection, and 0.25s is better indicated for this finality / Doutorado / Radiologia Odontologica / Doutor em Radiologia Odontológica
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Avaliação do desempenho de duas escalas de classificação de risco familiar e sua aplicação na saúde bucal / Performance evaluation of two scales for the classification of familial risk and its application in oral healthRocha, Vinício Felipe Brasil, 1984- 25 August 2018 (has links)
Orientador: Glaucia Maria Bovi Ambrosano / Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba / Made available in DSpace on 2018-08-25T23:47:50Z (GMT). No. of bitstreams: 1
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Previous issue date: 2014 / Resumo: Escalas de risco familiar são empregadas com a finalidade de estratificar o grau de vulnerabilidade de famílias ao adoecimento e desta forma priorizar a atenção àquelas com maiores necessidades. Este estudo transversal analítico teve por objetivo avaliar o desempenho de dois instrumentos de classificação de risco familiar, utilizados na atenção primária à saúde, verificando o poder discriminante dos mesmos tendo como desfecho a necessidade de tratamento odontológico. A amostra probabilística foi constituída por 1112 adolescentes de 15 a 19 anos de 34 Unidades de Saúde da Família e 21 escolas públicas da cidade de Piracicaba-SP. Após aplicação da ficha A do Sistema de Informação da Atenção Básica (SIAB), realizou-se a classificação de risco segundo a Escala de Coelho e Savassi (ECS) e a Escala Critério Universidade Federal do Espírito Santo (EUFES). A variável de desfecho "necessidade de tratamento odontológico" foi mensurada por meio de exame clínico realizado por dentistas previamente treinados e calibrados utilizando os indicadores propostos pela Organização Mundial da Saúde. Os dados foram analisados pela sensibilidade, especificidade e área sob a curva ROC. Evidenciou-se que a escala EUFES apresentou sensibilidade de 0,78 (IC95%: 0,75-0,82), especificidade de 0,35 (IC95%: 0,32-0,39), área sob a curva ROC (AUC) de 0,57 (IC95%: 0,54-0,61) e associação estatisticamente significantes (p<0,001) entre os diferentes níveis de risco (menor, médio, máximo) e a necessidade de tratamento odontológico. Já a ECS mostrou sensibilidade de 0,16 (IC95%: 0,13-0,20), especificidade de 0,90 (IC95%: 0,88-0,92), AUC de 0,53 (IC95%: 0,49-0,56) e relação estatisticamente significante somente para o menor e médio risco (p=0,01). Conclui-se assim que para identificação de pelo menos um indivíduo do núcleo familiar com necessidade de tratamento odontológico, a Escala EUFES demonstrou desempenho superior nos testes de associação e sensibilidade. Entretanto, considerando a área sob a curva ROC, verificou-se que os dois instrumentos possuem baixa capacidade de discriminação, indicando que novas escalas devem ser estudadas, a fim de se estabelecer um instrumento que melhor favoreça a organização da demanda programática dos serviços de saúde bucal / Abstract: Scales of familial risk are employed in order to stratify the degree of vulnerability of families to illness and thus prioritize attention to those most in need. This analytical cross-sectional study aimed to evaluate the performance of two instruments familial risk classification used in primary health care, checking the discriminating power of the as end the need for dental treatment. A random sample of 1112 adolescents 15-19 years of 34 Family Health Units and 21 public schools in Piracicaba-SP. After applying Record A Information System for Primary Care (SIAB), held the risk classification according to the Scale of Coelho and Savassi (ECS) and the Scale Criterion University Federal of Espírito Santo (EUFES). The outcome variable "need for dental treatment" was assessed by clinical examination performed by previously trained and calibrated dentists using the indicators proposed by WHO. Data were analyzed for sensitivity, specificity and area under the ROC curve. It was evident that the EUFES scale had a sensitivity of 0.78 (95% CI: 0.75 to 0.82), specificity 0.35 (95% CI: 0.32 to 0.39), area under the ROC curve AUC 0.57 (95% CI: 0.54 to 0.61) and statistically significant association (p<0.001) between the different risk levels (lower, middle, upper) and the need for dental treatment. Have ECS showed a sensitivity of 0.16 (95% CI: 0.13 to 0.20), specificity 0.90 (95% CI: 0.88 to 0.92), AUC of 0.53 (95% CI: 0 from 0.49 to 0.56) and statistically significant only for the lower and medium risk (p=0.01) relationship. It follows therefore that to identify at least one individual of the family unit in need of dental treatment Scale EUFES demonstrated superior performance in the association and sensitivity tests. However, considering the area under the ROC curve, it was found that the two instruments have low discrimination capacity, indicating that new scales should be studied in order to establish an instrument that best promotes the organization's programmatic demand for services health oral / Mestrado / Odontologia em Saude Coletiva / Mestre em Odontologia em Saúde Coletiva
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Avaliação do desempenho de modelos preditivos no contexto de análise de sobrevivência / Evaluation of predictive models in survival analysis.Tiago Mendonça dos Santos 17 May 2013 (has links)
Modelos estatísticos com objetivos preditivos são frequentemente aplicados como ferramentas no processo de tomadas de decisão em diversas áreas. Uma classe importante de modelos estatísticos é composta por modelos de análise de sobrevivência. Duas quantidades são de interesse nessa classe: o tempo até o instante do evento de interesse ou o status para um determinado instante de tempo fixado. Aplicações importantes desses modelos incluem a identificação de novos marcadores para certas doenças e definição de qual terapia será mais adequada de acordo com o paciente. Os marcadores utilizados podem ser dados por biomarcadores, assim como por marcadores baseados em modelos de regressão. Um exemplo de marcador baseado em modelos de regressão é dado pelo preditor linear. Ainda que a utilização de modelos de sobrevivência com objetivos preditivos seja de suma importância, a literatura nesse assunto é muito esparsa e não há consenso na forma de se avaliar o desempenho preditivo desses. Esse trabalho pretende reunir e comparar diferentes abordagens de se avaliar o desempenho preditivo de modelos de sobrevivência. Essa avaliação é feita principalmente utilizando-se funções de perda para o tempo de sobrevivência e quantidades associadas a diferentes definições de curva ROC para o status. Para a comparação dessas diferentes metodologias foi feito um estudo de simulação e no final aplicou-se essas técnicas em um conjunto de dados de um estudo do Instituto do Câncer de São Paulo. / In many fields, predictive models are often applied as a helpful tool in the decision making process. An important class of predictive models is composed by survival models. Two quantities of special interest in these class are: time until the occurrence of a specified event and survival status for a fixed moment of time. Important applications of these models include new markers identification for certain diseases, as well as defining which therapy is the most appropriated for a patient. Markers can be given by biomarkers, but they can also be derived from regression models. An example of regression models based markers is the linear predictor. Despite the importance of survival models applications with predictive goals, literature is this subject is very sparse and there is no agreement on the best methodology to evaluate predictive performance of these models. In this work we intend to assemble and to compare different methodologies for assessing the predictive performance of survival models. This assessment is made mainly with loss functions for the survival time and ROC curve associated quantities for status. An simulation study was done in order to compare these different methodologies, which were also applied to a study about survival of patients at ICU of ICESP (Instituto do Câncer de São Paulo)
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Méthodes d'apprentissage statistique pour le ranking : théorie, algorithmes et applications / Statistical learning methods for ranking : theory, algorithms and applicationsRobbiano, Sylvain 19 June 2013 (has links)
Le ranking multipartite est un problème d'apprentissage statistique qui consiste à ordonner les observations qui appartiennent à un espace de grande dimension dans le même ordre que les labels, de sorte que les observations avec le label le plus élevé apparaissent en haut de la liste. Cette thèse vise à comprendre la nature probabiliste du problème de ranking multipartite afin d'obtenir des garanties théoriques pour les algorithmes de ranking. Dans ce cadre, la sortie d'un algorithme de ranking prend la forme d'une fonction de scoring, une fonction qui envoie l'espace des observations sur la droite réelle et l'ordre finale est construit en utilisant l'ordre induit par la droite réelle. Les contributions de ce manuscrit sont les suivantes : d'abord, nous nous concentrons sur la caractérisation des solutions optimales de ranking multipartite. Le deuxième thème de recherche est la conception d'algorithmes pour produire des fonctions de scoring. Nous proposons deux méthodes, la première utilisant une procédure d'agrégation, la deuxième un schema d'approximation. Enfin, nous revenons au problème de ranking binaire afin d'établir des vitesse minimax adaptives de convergences. / Multipartite ranking is a statistical learning problem that consists in ordering observations that belong to a high dimensional feature space in the same order as the labels, so that the observations with the highest label appear at the top of the list. This work aims to understand the probabilistic nature of the multipartite ranking problem in order to obtain theoretical guarantees for ranking algorithms. In this context, the output of a ranking algorithm takes the form of a scoring function, a function that maps the space of the observation to the real line which order is induced using the values on the real line. The contributions of this manuscript are the following : First, we focus on the characterization of optimal solutions to multipartite ranking. The second research theme is the design of algorithms to produce scoring functions. We offer two methods, the first using an aggregation procedure, the second an approximation scheme. Finally, we return to the binary ranking problem to establish adaptive minimax rate of convergence.
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The Democratic Progressive Party: Self-regulation of Secessionist RhetoricO'Neal, Brandon 01 January 2016 (has links)
Ever since the formation of the Democratic Progressive Party in 1986, the party campaigned on Taiwanese nationalism and de jure independence. It was the party in Taiwan known for its unwavering stance in the “One China Policy”: it recognizes itself as the sole legitimate China. In light of the 2016 presidential elections, the DPP lead by Tsai Ing-Wen changed their usual secessionist rhetoric towards China to one that is much more moderate in stance. Tsai Ing-Wen has pledged to “maintain the cross-strait status quo”, a sharp contrast in opinion for the party. How can this change be explained? Is the Democratic Progressive Party of Taiwan self-regulating its language? What is the DPP self-regulating in response to? This study will look at whether the pressure is coming internally from the constituency or externally from China's military and economic pressure.
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Making diagnoses with multiple tests under no gold standardZhang, Jingyang 01 May 2012 (has links)
In many applications, it is common to have multiple diagnostic tests on each subject. When there are multiple tests available, combining tests to incorporate information from various aspects in subjects may be necessary in order to obtain a better diagnostic. For continuous tests, in the presence of a gold standard, we could combine the tests linearly (Su and Liu, 1993) or sequentially (Thompson, 2003), or using the risk score as studied by McIntosh and Pepe (2002). The gold standard, however, is not always available in practice. This dissertation concentrates on deriving classification methods based on multiple tests in the absence of a gold standard. Motivated by a lab data set consisting of two tests testing for an antibody in 100 blood samples, we first develop a mixture model of four bivariate normal distributions with the mixture probabilities depending on a two-stage latent structure. The proposed two-stage latent structure is based on the biological mechanism of the tests. A Bayesian classification method incorporating the available prior information is derived utilizing Bayesian decision theory. The proposed method is illustrated by the motivating example, and the properties of the estimation and the classification are described via simulation studies. Sensitivity to the choice of the prior distribution is also studied. We also investigate a general problem of combining multiple continuous tests without any gold standard or a reference test. We thoroughly study the existing methods for combining multiple tests and develop optimal classification rules corresponding to the methods accommodating the situation without a gold standard. We justify the proposed methods both theoretically and numerically through exten- sive simulation studies and illustrate the methods with the motivating example. In the end, we conclude the thesis with remarks and some interesting open questions extended from the dissertation.
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A Comparative Study Of Artificial Neural Networks And Info Fuzzy Networks On Their Use In Software TestingAgarwal, Deepam 12 May 2004 (has links)
It is very important that the software being delivered to the user is reliable and fault free. This makes software testing one of the most important phases in the software development life cycle. The problem being faced by everyone is the time it takes to test the software, which is normally huge. An important part of the software testing process is running and evaluating test scenarios. The objective of this part is to evaluate how well the application under test conforms to its specifications. One of the ways to achieve this is to generate the test cases and make use of the test oracle (a human expert) to determine whether a given test case exposes a fault. This procedure consumes a lot of time. Using an automated oracle can contribute towards the reduction in software testing time which helps in the reduction of the cost of the testing process.
The use of Artificial Neural Networks (ANN) and Info-Fuzzy Networks (IFN) for test case selection and evaluation has already been explored. In this thesis these two approaches are compared on their use as an automated oracle.
An ROC Analysis is done to compare the two approaches. The execution times of both the approaches are also compared. For comparison, three applications have been used. The basic methodology behind the use of IFN or ANN is to train the network on randomly generated test cases executed with a stable version of the software. This trained network is then used as an oracle for evaluating the correctness of the output produced by new and possibly faulty versions of the stable software. The outputs from the oracle i.e. IFN or ANN and faulty versions of the software system are compared with that of the original version to evaluate the outputs generated by new version of the software.
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Empirical Likelihood Confidence Intervals for ROC Curves with Missing DataAn, Yueheng 25 April 2011 (has links)
The receiver operating characteristic, or the ROC curve, is widely utilized to evaluate the diagnostic performance of a test, in other words, the accuracy of a test to discriminate normal cases from diseased cases. In the biomedical studies, we often meet with missing data, which the regular inference procedures cannot be applied to directly. In this thesis, the random hot deck imputation is used to obtain a 'complete' sample. Then empirical likelihood (EL) confidence intervals are constructed for ROC curves. The empirical log-likelihood ratio statistic is derived whose asymptotic distribution isproved to be a weighted chi-square distribution. The results of simulation study show that the EL confidence intervals perform well in terms of the coverage probability and the average length for various sample sizes and response rates.
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