143 resultados para SOCIETY CLASSIFICATION CRITERIA
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A síndrome metabólica (SM) consiste em um conjunto de fatores de risco cardiovascular relacionados à obesidade abdominal e à resistência à insulina, refletindo no aumento da glicemia e da pressão arterial e na ocorrência de dislipidemia. Critérios recentes utilizados para a classificação da síndrome consideram a circunferência da cintura e a pressão arterial elevadas, pré-diabetes, hipertrigliceridemia e HDL colesterol reduzido. A SM pode aumentar consideravelmente o risco de desenvolvimento e de mortalidade por doenças e agravos não transmissíveis, como diabetes e doenças cardiovasculares. Sua ocorrência é multifatorial, envolvendo aumento ponderal, alimentação inadequada, inatividade física, predisposição genética e tabagismo. Ações preventivas mostram-se mais efetivas para a diminuição de riscos, quando comparadas ao tratamento de suas consequências, sendo importante a promoção da alimentação saudável, que envolve incentivo ao consumo de fibras e de gorduras insaturadas e moderação das saturadas e trans e de sódio
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Background: Coronary artery disease (CAD) is among the main causes of death in developed countries, and diet and lifestyle can influence CAD incidence. Objective: To evaluate the association of coronary artery disease risk score with dietary, anthropometric and biochemical components in adults clinically selected for a lifestyle modification program. Methods: 362 adults (96 men, 266 women, 53.9 +/- 9.4 years) fulfilled the inclusion criteria by presenting all the required data. The Framingham score was calculated and the IV Brazilian Guideline on Dyslipidemia and Prevention of Atherosclerosis was adopted for classification of the CAD risks. Anthropometric assessments included waist circumference (WC), body fat and calculated BMI (kg/m(2)) and muscle-mass index (MMI kg/m(2)). Dietary intake was estimated through 24 h dietary recall. Fasting blood was used for biochemical analysis. Metabolic Syndrome (MS) was diagnosed using NCEP-ATPIII (2001) criteria. Logistic regression was used to determine the odds of CAD risks according to the altered components of MS, dietary, anthropometric, and biochemical components. Results: For a sample with a BMI 28.5 +/- 5.0 kg/m(2) the association with lower risk (<10% CAD) were lower age (<60 years old), and plasma values of uric acid. The presence of MS within low, intermediary, and high CAD risk categories was 30.8%, 55.5%, and 69.8%, respectively. The independent risk factors associated with CAD risk score was MS and uric acid, and the protective factors were recommended intake of saturated fat and fiber and muscle mass index. Conclusion: Recommended intake of saturated fat and dietary fiber, together with proper muscle mass, are inversely associated with CAD risk score. On the other hand, the presence of MS and high plasma uric acid are associated with CAD risk score.
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This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.
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Background: Bipolar Disorder (BD) is a chronic, recurrent and highly prevalent illness. Despite the need for correct diagnosis to allow proper treatment, studies have shown that reaching a diagnosis can take up to ten years due to the lack of recognition of the broader presentations of BD. Frequent comorbidities with other psychiatric disorders are a major cause of misdiagnosis and warrant thorough evaluation. Methods/Design: ESPECTRA (Occurrence of Bipolar Spectrum Disorders in Eating Disorder Patients) is a single-site cross-sectional study involving a comparison group, designed to evaluate the prevalence of bipolar spectrum in an eating disorder sample. Women aged 18-45 years will be evaluated using the SCID-P and Zurich criteria for diagnosis and the HAM-D, YOUNG, SCI-MOODS, HCL-32, BIS-11, BSQ, WHOQoL and EAS instruments for rating symptoms and measuring clinical correlates. Discussion: The classificatory systems in psychiatry are based on categorical models that have been criticized for simplifying the diagnosis and leading to an increase in comorbidities. Some dimensional approaches have been proposed aimed at improving the validity and reliability of psychiatric disorder assessments, especially in conditions with high rates of comorbidity such as BD and Eating Disorder (ED). The Bipolar Spectrum (BS) remains under-recognized in clinical practice and its definition is not well established in current diagnostic guidelines. Broader evaluation of psychiatric disorders combining categorical and dimensional views could contribute to a more realistic understanding of comorbidities and help toward establishing a prognosis.
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Background. Antilipoprotein lipase (anti-LPL) antibodies were described in rheumatic diseases. In systemic lupus erythematosus they were highly associated with inflammatory markers and dyslipidemia, and may ultimately contribute to vascular damage. The relevance of this association in Takayasu's arteritis, which is characterized by major inflammatory process affecting vessels, has not been determined. Objectives. To analyze the presence of anti-LPL antibodies in patients with Takayasu's arteritis and its association with inflammatory markers and lipoprotein risk levels. Methods. Thirty sera from patients with Takayasu's arteritis, according to ACR criteria, were consecutively included. IgG anti-LPL was detected by a standard ELISA. Lipoprotein risk levels were evaluated according to NCEP/ATPIII. Inflammatory markers included ESR and CRP values. Results. Takayasu's arteritis patients had a mean age of 34 years old and all were females. Half of the patients presented high ESR and 60% elevated CRP. Lipoprotein NCEP risk levels were observed in approximately half of the patients: 53% for total cholesterol, 43% for triglycerides, 16% for HDL-c and 47% for LDL-c. In spite of the high frequency of dyslipidemia and inflammatory markers in these patients no anti-LPL were detected. Conclusions. The lack of anti-LPL antibodies in Takayasu's disease implies distinct mechanisms underlying dyslipidemia compared to systemic lupus erythematosus. Copyright (C) 2009 Jozelio Freire de Carvalho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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AIM: To compare the histologic features of the liver in intrahepatic neonatal cholestasis (IHNC) with infectious, genetic-endocrine-metabolic, and idiopathic etiologies. METHODS: Liver biopsies from 86 infants with IHNC were evaluated. The inclusion criteria consisted of jaundice beginning at 3 mo of age and a hepatic biopsy during the 1st year of life. The following histologic features were evaluated: cholestasis, eosinophilia, giant cells, erythropoiesis, siderosis, portal fibrosis, and the presence of a septum. RESULTS: Based on the diagnosis, patients were classified into three groups: group 1 (infectious; n = 18), group 2 (genetic-endocrine-metabolic; n = 18), and group 3 (idiopathic; n = 50). There were no significant differences with respect to the following variables: cholestasis, eosinophilia, giant cells, siderosis, portal fibrosis, and presence of a septum. A significant difference was observed with respect to erythropoiesis, which was more severe in group 1 (Fisher's exact test, P = 0.016). CONCLUSION: A significant difference was observed in IHNC of infectious etiology, in which erythropoiesis was more severe than that in genetic-endocrine-metabolic and idiopathic etiologies, whereas there were no significant differences among cholestasis, eosinophilia, giant cells, siderosis, portal fibrosis, and the presence of a septum. (C) 2009 The WIG Press and Baishideng. All rights reserved.
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An in vivo study was conducted to verify the ability of laser fluorescence (LF) to assess the activity status of occlusal caries in primary teeth, using different air-drying times. Occlusal sites (707) were examined using LF (DIAGNOdent) after air-drying for 3 s and 15 s, and the difference between readings (DIF15 s-3 s) was calculated. For concurrent validation of LF, visual criteria-Nyvad (NY) and Lesion Activity Assessment associated with the International Caries Detection and Assessment System (LAA-ICDAS)-were the reference standards for lesion activity. Histological exam using a pH-indicator dye (0.1% methyl red) was performed in 46 exfoliated/extracted teeth for criterion validation. LF readings and DIF15 s-3 s were compared using Kruskall-Wallis and Mann-Whitney tests. Receiver operating characteristic analyses were performed and validity parameters calculated, considering the caries activity assessment. Using NY, active lesions (3 s: 30.0 +/- 29.3; 15 s: 34.2 +/- 30.6) presented higher LF readings than inactive lesions (3 s: 17.0 +/- 16.3; 15 s: 19.2 +/- 17.3; p <0.05), different from LAA-ICDAS. Active cavitated caries resulted in higher LF readings (3 s: 50.3 +/- 3.5; 15 s: 54.7 +/- 30.2) than inactive cavitated caries (3 s: 19.9 +/- 16.3; 15 s: 22.8 +/- 16.8). Therefore, LF can distinguish cavitated active and inactive lesions classified by NY, but not by LAA-ICDAS; however, this difference might be related to the visual system rather than to LF. The air-drying time could be an alternative to improve the caries activity assessment; however, longer air-drying time is suggested to be tested subsequently. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3463007]
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We present a new insight on NGC 6034 and UGC 842, two groups of galaxies previously reported in the literature as being fossil groups. The study is based on optical photometry and spectroscopy obtained with the CTIO Blanco telescope and Sloan Digital Sky Survey archival data. We find that NGC 6034 is embedded in a large structure, dominated by three rich clusters and other small groups. Its first and next four ranked galaxies have magnitude differences in the r band and projected distances which violate the optical criteria to classify it as a fossil group. We confirm that the UGC 842 group is a fossil group, but with about half the velocity dispersion that is reported in previous works. The velocity distribution of its galaxies reveals the existence of two structures in its line of sight, one with sigma(nu) similar to 223 km s(-1) and another with sigma(nu) similar to 235 km s(-1), with a difference in velocity of similar to 820 km s(-1). The main structure is dominated by passive galaxies, while these represent similar to 60% of the second structure. The X-ray temperature for the intragroup medium of a group with such a velocity dispersion is expected to be kT similar to 0.5-1 keV, against the observed value of kT similar to 1.9 keV reported in the literature. This result makes UGC 842 a special case among fossil groups because (1) it represents more likely the interaction between two small groups, which warms the intragroup medium and/or (2) it could constitute evidence that member galaxies lost energy in the process of spiraling toward the group center, and decreased the velocity dispersion of the system. As far as we know, UGC 842 is the first low-mass fossil group studied in detail.
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Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.
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We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.
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Given a compact 2 dimensional manifold M we classify all continuous flows phi without wandering points on M. This classification is performed by finding finitely many pairwise disjoint open phi-invariant subsets {U(1), U(2), ..., U(n)} of M such that U(i=1)(n) (U(i)) over bar = M and each U(i) is either a suspension of an interval exchange transformation, or a maximal open cylinder made up of closed trajectories of phi.
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Multispectral widefield optical imaging has the potential to improve early detection of oral cancer. The appropriate selection of illumination and collection conditions is required to maximize diagnostic ability. The goals of this study were to (i) evaluate image contrast between oral cancer/precancer and non-neoplastic mucosa for a variety of imaging modalities and illumination/collection conditions, and (ii) use classification algorithms to evaluate and compare the diagnostic utility of these modalities to discriminate cancers and precancers from normal tissue. Narrowband reflectance, autofluorescence, and polarized reflectance images were obtained from 61 patients and 11 normal volunteers. Image contrast was compared to identify modalities and conditions yielding greatest contrast. Image features were extracted and used to train and evaluate classification algorithms to discriminate tissue as non-neoplastic, dysplastic, or cancer; results were compared to histologic diagnosis. Autofluorescence imaging at 405-nm excitation provided the greatest image contrast, and the ratio of red-to-green fluorescence intensity computed from these images provided the best classification of dysplasia/cancer versus non-neoplastic tissue. A sensitivity of 100% and a specificity of 85% were achieved in the validation set. Multispectral widefield images can accurately distinguish neoplastic and non-neoplastic tissue; however, the ability to separate precancerous lesions from cancers with this technique was limited. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3516593]
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Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.
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The problem of semialgebraic Lipschitz classification of quasihomogeneous polynomials on a Holder triangle is studied. For this problem, the ""moduli"" are described completely in certain combinatorial terms.
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This paper is a continuation and a complement of our previous work on isomorphic classification of some spaces of compact operators. We improve the main result concerning extensions of the classical isomorphic classification of the Banach spaces of continuous functions on ordinals. As an application, fixing an ordinal a and denoting by X(xi), omega(alpha) <= xi < omega(alpha+1), the Banach space of all X-valued continuous functions defined in the interval of ordinals [0,xi] and equipped with the supremum, we provide complete isomorphic classifications of some Banach spaces K(X(xi),Y(eta)) of compact operators from X(xi) to Y(eta), eta >= omega. It is relatively consistent with ZFC (Zermelo-Fraenkel set theory with the axiom of choice) that these results include the following cases: 1.X* contains no copy of c(0) and has the Mazur property, and Y = c(0)(J) for every set J. 2. X = c(0)(I) and Y = l(q)(J) for any infinite sets I and J and 1 <= q < infinity. 3. X = l(p)(I) and Y = l(q)(J) for any infinite sets I and J and 1 <= q < p < infinity.