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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
Publicado em 01/12/2012 EN
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
Fonte: Faculdade de Saúde Pública da Universidade de São Paulo Publicador: Faculdade de Saúde Pública da Universidade de São Paulo
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2014 EN
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.17%
We consider the problem of recovering a vector $\beta_o \in \mathbb{R}^p$ from $n$ random and noisy linear observations $y= X\beta_o + w$, where $X$ is the measurement matrix and $w$ is noise. The LASSO estimate is given by the solution to the optimization problem $\hat{\beta}_{\lambda} = \arg \min_{\beta} \frac{1}{2} \|y-X\beta\|_2^2 + \lambda \| \beta \|_1$. Among the iterative algorithms that have been proposed for solving this optimization problem, approximate message passing (AMP) has attracted attention for its fast convergence. Despite significant progress in the theoretical analysis of the estimates of LASSO and AMP, little is known about their behavior as a function of the regularization parameter $\lambda$, or the thereshold parameters $\tau^t$. For instance the following basic questions have not yet been studied in the literature: (i) How does the size of the active set $\|\hat{\beta}^\lambda\|_0/p$ behave as a function of $\lambda$? (ii) How does the mean square error $\|\hat{\beta}_{\lambda} - \beta_o\|_2^2/p$ behave as a function of $\lambda$? (iii) How does $\|\beta^t - \beta_o \|_2^2/p$ behave as a function of $\tau^1, \ldots, \tau^{t-1}$? Answering these questions will help in addressing practical challenges regarding the optimal tuning of $\lambda$ or $\tau^1...

Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

Drton, Mathias; Eichler, Michael
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.12%
The AMP Markov property is a recently proposed alternative Markov property for chain graphs. In the case of continuous variables with a joint multivariate Gaussian distribution, it is the AMP rather than the earlier introduced LWF Markov property that is coherent with data-generation by natural block-recursive regressions. In this paper, we show that maximum likelihood estimates in Gaussian AMP chain graph models can be obtained by combining generalized least squares and iterative proportional fitting to an iterative algorithm. In an appendix, we give useful convergence results for iterative partial maximization algorithms that apply in particular to the described algorithm.; Comment: 15 pages, article will appear in Scandinavian Journal of Statistics

Marginal AMP Chain Graphs

Peña, Jose M.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.05%
We present a new family of models that is based on graphs that may have undirected, directed and bidirected edges. We name these new models marginal AMP (MAMP) chain graphs because each of them is Markov equivalent to some AMP chain graph under marginalization of some of its nodes. However, MAMP chain graphs do not only subsume AMP chain graphs but also multivariate regression chain graphs. We describe global and pairwise Markov properties for MAMP chain graphs and prove their equivalence for compositional graphoids. We also characterize when two MAMP chain graphs are Markov equivalent. For Gaussian probability distributions, we also show that every MAMP chain graph is Markov equivalent to some directed and acyclic graph with deterministic nodes under marginalization and conditioning on some of its nodes. This is important because it implies that the independence model represented by a MAMP chain graph can be accounted for by some data generating process that is partially observed and has selection bias. Finally, we modify MAMP chain graphs so that they are closed under marginalization for Gaussian probability distributions. This is a desirable feature because it guarantees parsimonious models under marginalization.; Comment: Changes from v1 to v2: Discussion section got extended. Changes from v2 to v3: New Sections 3 and 5. Changes from v3 to v4: Example 4 added to discussion section. Changes from v4 to v5: None. Changes from v5 to v6: Some minor and major errors have been corrected. The latter include the definitions of descending route and pairwise separation base...

State Evolution for General Approximate Message Passing Algorithms, with Applications to Spatial Coupling

Javanmard, Adel; Montanari, Andrea
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26%
We consider a class of approximated message passing (AMP) algorithms and characterize their high-dimensional behavior in terms of a suitable state evolution recursion. Our proof applies to Gaussian matrices with independent but not necessarily identically distributed entries. It covers --in particular-- the analysis of generalized AMP, introduced by Rangan, and of AMP reconstruction in compressed sensing with spatially coupled sensing matrices. The proof technique builds on the one of [BM11], while simplifying and generalizing several steps.; Comment: 29 pages, 1 figure, minor updates in citations

Phase Transitions in Sparse PCA

Lesieur, Thibault; Krzakala, Florent; Zdeborova, Lenka
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/03/2015
Relevância na Pesquisa
26.05%
We study optimal estimation for sparse principal component analysis when the number of non-zero elements is small but on the same order as the dimension of the data. We employ approximate message passing (AMP) algorithm and its state evolution to analyze what is the information theoretically minimal mean-squared error and the one achieved by AMP in the limit of large sizes. For a special case of rank one and large enough density of non-zeros Deshpande and Montanari [1] proved that AMP is asymptotically optimal. We show that both for low density and for large rank the problem undergoes a series of phase transitions suggesting existence of a region of parameters where estimation is information theoretically possible, but AMP (and presumably every other polynomial algorithm) fails. The analysis of the large rank limit is particularly instructive.; Comment: 6 pages, 3 figures

Parameterless Optimal Approximate Message Passing

Mousavi, Ali; Maleki, Arian; Baraniuk, Richard G.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 31/10/2013
Relevância na Pesquisa
26.04%
Iterative thresholding algorithms are well-suited for high-dimensional problems in sparse recovery and compressive sensing. The performance of this class of algorithms depends heavily on the tuning of certain threshold parameters. In particular, both the final reconstruction error and the convergence rate of the algorithm crucially rely on how the threshold parameter is set at each step of the algorithm. In this paper, we propose a parameter-free approximate message passing (AMP) algorithm that sets the threshold parameter at each iteration in a fully automatic way without either having an information about the signal to be reconstructed or needing any tuning from the user. We show that the proposed method attains both the minimum reconstruction error and the highest convergence rate. Our method is based on applying the Stein unbiased risk estimate (SURE) along with a modified gradient descent to find the optimal threshold in each iteration. Motivated by the connections between AMP and LASSO, it could be employed to find the solution of the LASSO for the optimal regularization parameter. To the best of our knowledge, this is the first work concerning parameter tuning that obtains the fastest convergence rate with theoretical guarantees.

Characterizing Markov equivalence classes for AMP chain graph models

Andersson, Steen A.; Perlman, Michael D.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 03/07/2006
Relevância na Pesquisa
36.32%
Chain graphs (CG) ($=$ adicyclic graphs) use undirected and directed edges to represent both structural and associative dependences. Like acyclic directed graphs (ADGs), the CG associated with a statistical Markov model may not be unique, so CGs fall into Markov equivalence classes, which may be superexponentially large, leading to unidentifiability and computational inefficiency in model search and selection. It is shown here that, under the Andersson--Madigan--Perlman (AMP) interpretation of a CG, each Markov-equivalence class can be uniquely represented by a single distinguished CG, the AMP essential graph, that is itself simultaneously Markov equivalent to all CGs in the AMP Markov equivalence class. A complete characterization of AMP essential graphs is obtained. Like the essential graph previously introduced for ADGs, the AMP essential graph will play a fundamental role for inference and model search and selection for AMP CG models.; Comment: Published at http://dx.doi.org/10.1214/009053606000000173 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

The Noise-Sensitivity Phase Transition in Compressed Sensing

Donoho, David L.; Maleki, Arian; Montanari, Andrea
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 07/04/2010
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 24/04/2012
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
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.
Fonte: Universidade Cornell Publicador: Universidade Cornell
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
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 17/06/2014
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
Fonte: Universidade Cornell Publicador: Universidade Cornell
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
Fonte: Universidade de São Paulo. Faculdade de Medicina Publicador: Universidade de São Paulo. Faculdade de Medicina
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; Formato: application/pdf
Publicado em 18/12/2012 POR
Relevância na Pesquisa
35.88%
Vision is the main skill for the driving act and a good visual accuity is mandatory to be a professional driver. Objective: to evaluate the visual conditions in a group of 100 professional drivers of Campinas, SP. Methods: This retrospective study rewied records of 100 active professional drivers whose ophthalmologic examination was performed at Fundação Dr. João Penido Burnier de Campinas, a public and private ophthalmologic clinic, from 2006 to 2011. Results: Driver’s mean age was 52.8 years and all were males. They came to ophthalmologic evaluation because of periodic evaluation (36.8%) and impaired visual accuity (33.6%). Systemic comorbidities were presented by 44%, with predominance of diabetes and systemic arterial hypertension. The visual accuity was 100% in 47% and equal or higher than 0.66 in 69.4%, being each eye avaluated separately. The visual accuity was less than 0.5 in one eye in 22.1%. The most prevalent ophthalmologic disease was cristalin opacification (44.2%), with cataract surgery indication in 16.8%. Glaucoma was identified in 3.1%, pterigium in 5.2%, pinguecula in 6.3% and increased intraocular pression in 8.6%. Fundoscopy was considered normal in 53.6% and the main pathologies were suspect optic nerve escavation (10.5%)...

Evaluation of dengue fever reports during an epidemic, Colombia

Romero-Vega,Liliana; Pacheco,Oscar; la Hoz-Restrepo,Fernando de; Díaz-Quijano,Fredi Alexander
Fonte: Faculdade de Saúde Pública da Universidade de São Paulo Publicador: Faculdade de Saúde Pública da Universidade de São Paulo
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2014 EN
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...