Página 1 dos resultados de 108 itens digitais encontrados em 0.005 segundos

## Gross Domestic Product (GDP) per capita and geographical distribution of ophthalmologists in Brazil

Carvalho,Regina de Souza; Diniz,Alice Selles; Lacerda,Fabrício Martins; Mello,Paulo Augusto de Arruda
Fonte: Conselho Brasileiro de Oftalmologia Publicador: Conselho Brasileiro de Oftalmologia
Tipo: Artigo de Revista Científica Formato: text/html
Relevância na Pesquisa
36.1%
PURPOSE: To assess the number of ophthalmologists in Brazil, their regional distribution, ophthalmologist/habitant ratio, and the relation between ophthalmologist and State Gross Domestic Product (GDP) per capita to aid public health policies. METHODS: An ecologic study was conducted. Data were obtained from the "Census 2011 Brazilian Ophthalmology Council", from "Demographic Census of Brazilian Institute of Geography and Statistics (IBGE) 2010 and from "Brazilian Regional Accounts, 2005-2009"- Ministry of Planning, Budget and Management - IBGE. RESULTS: The number of ophthalmologists in Brazil is 15,719. Considering the performance in more than one municipality, the number of ophthalmologists in service is 17,992, that is, one ophthalmologist for 10,601; the ophthalmologist/site ratio vary among the States from a minimum of 1/51,437 (Amapá) to a maximum of 1/4,279 (Distrito Federal). There is a correlation among State GDP per capita and the number of ophthalmologists/habitant: the higher the GDP per capita, the larger is the number of ophthalmologists acting in the State (p<0.0001). CONCLUSION: According to this study, there is no lack of Ophthalmologists in the country, but a distribution imbalance which leads to professional shortage in particular places. A higher concentration of ophthalmologists/inhabitants was noticed in States which the economic growth is higher...

## Evaluation of dengue fever reports during an epidemic, Colombia

Romero-Vega,Liliana; Pacheco,Oscar; la Hoz-Restrepo,Fernando de; Díaz-Quijano,Fredi Alexander
Tipo: Artigo de Revista Científica Formato: text/html
Relevância na Pesquisa
35.88%
OBJECTIVE To assess the validity of dengue fever reports and how they relate to the definition of case and severity. METHODS Diagnostic test assessment was conducted using cross-sectional sampling from a universe of 13,873 patients treated during the fifth epidemiological period in health institutions from 11 Colombian departments in 2013. The test under analyses was the reporting to the National Public Health Surveillance System, and the reference standard was the review of histories identified by active institutional search. We reviewed all histories of patients diagnosed with dengue fever, as well as a random sample of patients with febrile syndromes. The specificity and sensitivity of reports were estimated for this purpose, considering the inverse of the probability of being selected for weighting. The concordance between reporting and the findings of the active institutional search was calculated using Kappa statistics. RESULTS We included 4,359 febrile patients, and 31.7% were classified as compatible with dengue fever (17 with severe dengue fever; 461 with dengue fever and warning signs; 904 with dengue fever and no warning signs). The global sensitivity of reports was 13.2% (95%CI 10.9;15.4) and specificity was 98.4% (95%CI 97.9;98.9). Sensitivity varied according to severity: 12.1% (95%CI 9.3;14.8) for patients presenting dengue fever with no warning signs; 14.5% (95%CI 10.6;18.4) for those presenting dengue fever with warning signs...

## Every LWF and AMP chain graph originates from a set of causal models

Peña, Jose M.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.91%
This paper aims at justifying LWF and AMP chain graphs by showing that they do not represent arbitrary independence models. Specifically, we show that every chain graph is inclusion optimal wrt the intersection of the independence models represented by a set of directed and acyclic graphs under conditioning. This implies that the independence model represented by the chain graph can be accounted for by a set of causal models that are subject to selection bias, which in turn can be accounted for by a system that switches between different regimes or configurations.; Comment: Changes from v1 to v2: Major reorganization and correction of some errors. Changes from v2 to v3: Negligible changes

## Error AMP Chain Graphs

Peña, Jose M.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.05%
Any regular Gaussian probability distribution that can be represented by an AMP chain graph (CG) can be expressed as a system of linear equations with correlated errors whose structure depends on the CG. However, the CG represents the errors implicitly, as no nodes in the CG correspond to the errors. We propose in this paper to add some deterministic nodes to the CG in order to represent the errors explicitly. We call the result an EAMP CG. We will show that, as desired, every AMP CG is Markov equivalent to its corresponding EAMP CG under marginalization of the error nodes. We will also show that every EAMP CG under marginalization of the error nodes is Markov equivalent to some LWF CG under marginalization of the error nodes, and that the latter is Markov equivalent to some directed and acyclic graph (DAG) under marginalization of the error nodes and conditioning on some selection nodes. This is important because it implies that the independence model represented by an AMP CG can be accounted for by some data generating process that is partially observed and has selection bias. Finally, we will show that EAMP CGs are closed under marginalization. This is a desirable feature because it guarantees parsimonious models under marginalization.; Comment: In Proceedings of the 12th Scandinavian Conference on Artificial Intelligence (SCAI 2013)...

## Consistent Parameter Estimation for LASSO and Approximate Message Passing

Mousavi, Ali; Maleki, Arian; Baraniuk, Richard G.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.17%

## The Noise-Sensitivity Phase Transition in Compressed Sensing

Donoho, David L.; Maleki, Arian; Montanari, Andrea
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26%
Consider the noisy underdetermined system of linear equations: y=Ax0 + z0, with n x N measurement matrix A, n < N, and Gaussian white noise z0 ~ N(0,\sigma^2 I). Both y and A are known, both x0 and z0 are unknown, and we seek an approximation to x0. When x0 has few nonzeros, useful approximations are obtained by l1-penalized l2 minimization, in which the reconstruction \hxl solves min || y - Ax||^2/2 + \lambda ||x||_1. Evaluate performance by mean-squared error (MSE = E ||\hxl - x0||_2^2/N). Consider matrices A with iid Gaussian entries and a large-system limit in which n,N\to\infty with n/N \to \delta and k/n \to \rho. Call the ratio MSE/\sigma^2 the noise sensitivity. We develop formal expressions for the MSE of \hxl, and evaluate its worst-case formal noise sensitivity over all types of k-sparse signals. The phase space 0 < \delta, \rho < 1 is partitioned by curve \rho = \rhoMSE(\delta) into two regions. Formal noise sensitivity is bounded throughout the region \rho < \rhoMSE(\delta) and is unbounded throughout the region \rho > \rhoMSE(\delta). The phase boundary \rho = \rhoMSE(\delta) is identical to the previously-known phase transition curve for equivalence of l1 - l0 minimization in the k-sparse noiseless case. Hence a single phase boundary describes the fundamental phase transitions both for the noiseless and noisy cases. Extensive computational experiments validate the predictions of this formalism...

## Learning AMP Chain Graphs under Faithfulness

Peña, Jose M.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.17%
This paper deals with chain graphs under the alternative Andersson-Madigan-Perlman (AMP) interpretation. In particular, we present a constraint based algorithm for learning an AMP chain graph a given probability distribution is faithful to. We also show that the extension of Meek's conjecture to AMP chain graphs does not hold, which compromises the development of efficient and correct score+search learning algorithms under assumptions weaker than faithfulness.

## Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness: Extended Version

Peña, Jose M.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.08%
This paper deals with chain graphs under the Andersson-Madigan-Perlman (AMP) interpretation. In particular, we present a constraint based algorithm for learning an AMP chain graph a given probability distribution is faithful to. Moreover, we show that the extension of Meek's conjecture to AMP chain graphs does not hold, which compromises the development of efficient and correct score+search learning algorithms under assumptions weaker than faithfulness. We also introduce a new family of graphical models that consists of undirected and bidirected edges. We name this new family maximal covariance-concentration graphs (MCCGs) because it includes both covariance and concentration graphs as subfamilies. However, every MCCG can be seen as the result of marginalizing out some nodes in an AMP CG. We describe global, local and pairwise Markov properties for MCCGs and prove their equivalence. We characterize when two MCCGs are Markov equivalent, and show that every Markov equivalence class of MCCGs has a distinguished member. We present a constraint based algorithm for learning a MCCG a given probability distribution is faithful to. Finally, we present a graphical criterion for reading dependencies from a MCCG of a probability distribution that satisfies the graphoid properties...

## Factorization, Inference and Parameter Learning in Discrete AMP Chain Graphs

Peña, Jose M.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.05%
We address some computational issues that may hinder the use of AMP chain graphs in practice. Specifically, we show how a discrete probability distribution that satisfies all the independencies represented by an AMP chain graph factorizes according to it. We show how this factorization makes it possible to perform inference and parameter learning efficiently, by adapting existing algorithms for Markov and Bayesian networks. Finally, we turn our attention to another issue that may hinder the use of AMP CGs, namely the lack of an intuitive interpretation of their edges. We provide one such interpretation.

## From Denoising to Compressed Sensing

Metzler, Christopher A.; Maleki, Arian; Baraniuk, Richard G.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.17%
A denoising algorithm seeks to remove perturbations or errors from a signal. The last three decades have seen extensive research devoted to this arena, and as a result, today's denoisers are highly optimized algorithms that effectively remove large amounts of additive white Gaussian noise. A compressive sensing (CS) reconstruction algorithm seeks to recover a structured signal acquired using a small number of randomized measurements. Typical CS reconstruction algorithms can be cast as iteratively estimating a signal from a perturbed observation. This paper answers a natural question: How can one effectively employ a generic denoiser in a CS reconstruction algorithm? In response, in this paper, we develop a denoising-based approximate message passing (D-AMP) algorithm that is capable of high-performance reconstruction. We demonstrate that, for an appropriate choice of denoiser, D-AMP offers state-of-the-art CS recovery performance for natural images. We explain the exceptional performance of D-AMP by analyzing some of its theoretical features. A critical insight in our approach is the use of an appropriate Onsager correction term in the D-AMP iterations, which coerces the signal perturbation at each iteration to be very close to the white Gaussian noise that denoisers are typically designed to remove.

## Sparse Estimation with the Swept Approximated Message-Passing Algorithm

Manoel, Andre; Krzakala, Florent; Tramel, Eric W.; Zdeborová, Lenka
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.23%
Approximate Message Passing (AMP) has been shown to be a superior method for inference problems, such as the recovery of signals from sets of noisy, lower-dimensionality measurements, both in terms of reconstruction accuracy and in computational efficiency. However, AMP suffers from serious convergence issues in contexts that do not exactly match its assumptions. We propose a new approach to stabilizing AMP in these contexts by applying AMP updates to individual coefficients rather than in parallel. Our results show that this change to the AMP iteration can provide theoretically expected, but hitherto unobtainable, performance for problems on which the standard AMP iteration diverges. Additionally, we find that the computational costs of this swept coefficient update scheme is not unduly burdensome, allowing it to be applied efficiently to signals of large dimensionality.; Comment: 11 pages, 3 figures, implementation available at https://github.com/eric-tramel/SwAMP-Demo

## Approximate Message Passing with Restricted Boltzmann Machine Priors

Tramel, Eric W.; Drémeau, Angélique; Krzakala, Florent
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.12%
Approximate Message Passing (AMP) has been shown to be an excellent statistical approach to signal inference and compressed sensing problem. The AMP framework provides modularity in the choice of signal prior; here we propose a hierarchical form of the Gauss-Bernouilli prior which utilizes a Restricted Boltzmann Machine (RBM) trained on the signal support to push reconstruction performance beyond that of simple iid priors for signals whose support can be well represented by a trained binary RBM. We present and analyze two methods of RBM factorization and demonstrate how these affect signal reconstruction performance within our proposed algorithm. Finally, using the MNIST handwritten digit dataset, we show experimentally that using an RBM allows AMP to approach oracle-support performance.

## Avaliação oftalmológica de um grupo de motoristas profissionais de Campinas, São Paulo; Retrospective evaluation of 100 ophtamologic files of professional drivers in Campinas

Quagliato, Lucas Barasnevicius; Soares, Carla Beatriz Carneiro da Cunha; Soares, Marcus Vinícius Carneiro da Cunha; Faiman, Carla Júlia Segre
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; Formato: application/pdf