885 resultados para Bayesian ridge regression


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A common finding in patients with edentulous maxilla and partially dentate mandible is mainly the presence of flabbiness in the anterior edentulous alveolar ridge that can compromise the retention and stability of a denture. Thus, this case report presents the correction of a flabby ridge, using an auxiliary technique combining surgical excision and autogenous connective tissue grafting. The technique improved the quality of the osteomucosal support of the alveolar ridge and increased the vestibule deepness, whose result increased the success rate of the new conventional total prosthesis.

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The aim of this study was to evaluate the tendency of displacement of the supporting structures of the distal extension removable partial denture (DERPD) associated to the implant with different inclinations of alveolar ridge and implant localizations through a two-dimensional finite-element method. Sixteen mandibular models were fabricated, presenting horizontal, distally descending, distally ascending, or descending-ascending ridges. All models presented the left canine and were rehabilitated with conventional DERPD or implant-retained prosthesis with the ERA system. The models were obtained by the AutoCAD software and transferred to the finite-element software ANSYS 9.0 for analysis. A force of 50 N was applied on the cusp tips of the teeth, with 5 points of loading of 10 N. The results were visualized by displacement maps. For all ridge inclinations, the assembly of the DERPD with distal plate retained by an anterior implant exhibited the lowest requisition of the supporting structures. The highest tendency of displacement occurred in the model with distally ascending ridge with incisal rest. It was concluded that the association of the implant decreased the displacement of the DERPD, and the anterior positioning of the implant associated to the DERPD with the distal plate preserved the supporting structures for all ridges.

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Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

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It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of the current study is to evaluate fresh-frozen human bone allografts (FHBAs) used in vertical ridge augmentation clinically and by computed tomography, and to analyze the resulting bone formation and graft resorption. Sixteen FHBAs were grafted in the maxillae and mandibles of 9 patients. The FHBAs, which were provided by the Musculoskeletal Tissue Bank of Marilia Hospital (Unioss), were frozen at -80A degrees C. After 7 months, dental implants were placed and bone parameters were evaluated. Vertical bone formation was measured by computerized tomography before (T0) and at 7 months (T1) after the surgical procedure. Bone graft resorption was measured clinically from a landmark screw head using a periodontal probe. The results were analyzed by Student's t-test. Significant differences existed in the bone formation values at T0 and T1, with an average change of 4.03 +/- A 1.69 mm. Bone graft resorption values were 1.0 +/- A 0.82 mm (20%). Implants were placed with varying insertion torque values (35-45 Ncm), and achieved primary stability. This study demonstrates that FHBAs promote satisfactory vertical bone formation with a low resorption rates, good density, and primary implant stability.

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Objetivou-se comparar modelos de regressão aleatória com diferentes estruturas de variância residual, a fim de se buscar a melhor modelagem para a característica tamanho da leitegada ao nascer (TLN). Utilizaram-se 1.701 registros de TLN, que foram analisados por meio de modelo animal, unicaracterística, de regressão aleatória. As regressões fixa e aleatórias foram representadas por funções contínuas sobre a ordem de parto, ajustadas por polinômios ortogonais de Legendre de ordem 3. Para averiguar a melhor modelagem para a variância residual, considerou-se a heterogeneidade de variância por meio de 1 a 7 classes de variância residual. O modelo geral de análise incluiu grupo de contemporâneo como efeito fixo; os coeficientes de regressão fixa para modelar a trajetória média da população; os coeficientes de regressão aleatória do efeito genético aditivo-direto, do comum-de-leitegada e do de ambiente permanente de animal; e o efeito aleatório residual. O teste da razão de verossimilhança, o critério de informação de Akaike e o critério de informação bayesiano de Schwarz apontaram o modelo que considerou homogeneidade de variância como o que proporcionou melhor ajuste aos dados utilizados. As herdabilidades obtidas foram próximas a zero (0,002 a 0,006). O efeito de ambiente permanente foi crescente da 1ª (0,06) à 5ª (0,28) ordem, mas decrescente desse ponto até a 7ª ordem (0,18). O comum-de-leitegada apresentou valores baixos (0,01 a 0,02). A utilização de homogeneidade de variância residual foi mais adequada para modelar as variâncias associadas à característica tamanho da leitegada ao nascer nesse conjunto de dado.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

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Estudaram-se os processos de regressão ovariana e atresia folicular em cachara, Pseudoplatystoma fasciatum, mantida em cativeiro, na reprodução não induzida por hormônios. As características macro e microscópicas (diâmetro dos ovócitos e histologia) dos ovários foram descritas a cada 20 dias, em quatro estádios: na regressão inicial (Rg I - os primeiros 20 dias), na regressão intermediária (Rg II - do 21º ao 40º dia), na regressão final (Rg III - do 41º ao 80º dia) e na fase de recuperação ou de repouso II (R II - do 81º ao 150º dia). O experimento foi realizado do final de janeiro (verão-dias longos) a maio (outono-dias curtos). No início do experimento, as amostras apresentaram ovócitos com diâmetros que variaram de 437,5 a 1.187,5mm, sugerindo encontrarem-se nas fases perinucleolar, de maturação final e atrésicos. Aos 150 dias, os diâmetros atingiram os menores valores e pôde-se visualizar a zona radiata rompida e o vitelo reabsorvido. Concomitantemente, houve diminuição abrupta dos valores médios do índice gonadossomático, da temperatura da água, das horas de luz e de chuva. A involução gradual do longo processo foi dinâmica e complexa, afetando o êxito da desova (taxas de fertilização, de eclosão e de sobrevivência de larvas) e, conseqüentemente, o sistema produtivo.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.