946 resultados para Databases as Topic


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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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OBJECTIVE: To update trends in mortality from coronary heart diseases (CHD) and cerebrovascular diseases (CVD) over the period 1981-2004 in Europe, the USA, Latin America, Japan and other selected areas of the world. METHODS: Age-standardized mortality rates were derived from the World Health Organization database. Joinpoint analysis was used to identify significant changes in trends. RESULTS: In the European Union (27 countries), CHD mortality in men declined from 139/100,000 in 1985-1989 to 93/100,000 in 2000-2004 (-33%). In women, the fall was from 61/100,000 to 44/100,000 (-27%). In this area, a decline by over 30% was also registered in CVD mortality for both sexes. In the Russian Federation and other countries of the former Soviet Union, CHD rates in 2000-2004 were exceedingly high, around 380/100,000 men and 170/100,000 women in Russia, 430 for men and 240 for women in Ukraine, 420 and 200 in Belarus. For CVD, a similar situation was registered, with mortality rates of 226/100,000 for men and 159/100,000 for women in 2004 in the Russian Federation, and more than 24% increase since the late 1980s for men and 15% for women. CHD and CVD mortality continued to decline in most Latin American countries, Australia and other areas considered, including Asia (even if with marked differences). CONCLUSION: Although mortality from CHD and CVD continues to decline in several areas of the world including most countries of Europe and of the America providing data and Australia, unfavourable trends were still observed in the Russian Federation and other countries of the former Soviet Union, whose recent rates remain exceedingly high.

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INTRODUCTION No definitive data are available regarding the value of switching to an alternative TNF antagonist in rheumatoid arthritis patients who fail to respond to the first one. The aim of this study was to evaluate treatment response in a clinical setting based on HAQ improvement and EULAR response criteria in RA patients who were switched to a second or a third TNF antagonist due to failure with the first one. METHODS This was an observational, prospective study of a cohort of 417 RA patients treated with TNF antagonists in three university hospitals in Spain between January 1999 and December 2005. A database was created at the participating centres, with well-defined operational instructions. The main outcome variables were analyzed using parametric or non-parametric tests depending on the level of measurement and distribution of each variable. RESULTS Mean (+/- SD) DAS-28 on starting the first, second and third TNF antagonist was 5.9 (+/- 2.0), 5.1 (+/- 1.5) and 6.1 (+/- 1.1). At the end of follow-up, it decreased to 3.3 (+/- 1.6; Delta = -2.6; p > 0.0001), 4.2 (+/- 1.5; Delta = -1.1; p = 0.0001) and 5.4 (+/- 1.7; Delta = -0.7; p = 0.06). For the first TNF antagonist, DAS-28-based EULAR response level was good in 42% and moderate in 33% of patients. The second TNF antagonist yielded a good response in 20% and no response in 53% of patients, while the third one yielded a good response in 28% and no response in 72%. Mean baseline HAQ on starting the first, second and third TNF antagonist was 1.61, 1.52 and 1.87, respectively. At the end of follow-up, it decreased to 1.12 (Delta = -0.49; p < 0.0001), 1.31 (Delta = -0.21, p = 0.004) and 1.75 (Delta = -0.12; p = 0.1), respectively. Sixty four percent of patients had a clinically important improvement in HAQ (defined as > or = -0.22) with the first TNF antagonist and 46% with the second. CONCLUSION A clinically significant effect size was seen in less than half of RA patients cycling to a second TNF antagonist.

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Escherichia coli, Klebsiella pneumoniae, and Enterobacter spp. are a major cause of infections in hospitalised patients. The aim of our study was to evaluate rates and trends of resistance to third-generation cephalosporins and fluoroquinolones in infected patients, the trends in use for these antimicrobials, and to assess the potential correlation between both trends. The database of national point prevalence study series of infections and antimicrobial use among patients hospitalised in Spain over the period from 1999 to 2010 was analysed. On average 265 hospitals and 60,000 patients were surveyed per year yielding a total of 19,801 E. coli, 3,004 K. pneumoniae and 3,205 Enterobacter isolates. During the twelve years period, we observed significant increases for the use of fluoroquinolones (5.8%-10.2%, p<0.001), but not for third-generation cephalosporins (6.4%-5.9%, p=NS). Resistance to third-generation cephalosporins increased significantly for E. coli (5%-15%, p<0.01) and for K. pneumoniae infections (4%-21%, p<0.01) but not for Enterobacter spp. (24%). Resistance to fluoroquinolones increased significantly for E. coli (16%30%, p<0.01), for K. pneumoniae (5%-22%, p<0.01), and for Enterobacter spp. (6%-15%, p<0.01). We found strong correlations between the rate of fluoroquinolone use and the resistance to fluoroquinolones, third-generation cephalosporins, or co-resistance to both, for E. coli (R=0.97, p<0.01, R=0.94, p<0.01, and R=0.96, p<0.01, respectively), and for K. pneumoniae (R=0.92, p<0.01, R=0.91, p<0.01, and R=0.92, p<0.01, respectively). No correlation could be found between the use of third-generation cephalosporins and resistance to any of the latter antimicrobials. No significant correlations could be found for Enterobacter spp.. Knowledge of the trends in antimicrobial resistance and use of antimicrobials in the hospitalised population at the national level can help to develop prevention strategies.

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Previously published scientific papers have reported a negative correlation between drinking water hardness and cardiovascular mortality. Some ecologic and case-control studies suggest the protective effect of calcium and magnesium concentration in drinking water. In this article we present an analysis of this protective relationship in 538 municipalities of Comunidad Valenciana (Spain) from 1991-1998. We used the Spanish version of the Rapid Inquiry Facility (RIF) developed under the European Environment and Health Information System (EUROHEIS) research project. The strategy of analysis used in our study conforms to the exploratory nature of the RIF that is used as a tool to obtain quick and flexible insight into epidemiologic surveillance problems. This article describes the use of the RIF to explore possible associations between disease indicators and environmental factors. We used exposure analysis to assess the effect of both protective factors--calcium and magnesium--on mortality from cerebrovascular (ICD-9 430-438) and ischemic heart (ICD-9 410-414) diseases. This study provides statistical evidence of the relationship between mortality from cardiovascular diseases and hardness of drinking water. This relationship is stronger in cerebrovascular disease than in ischemic heart disease, is more pronounced for women than for men, and is more apparent with magnesium than with calcium concentration levels. Nevertheless, the protective nature of these two factors is not clearly established. Our results suggest the possibility of protectiveness but cannot be claimed as conclusive. The weak effects of these covariates make it difficult to separate them from the influence of socioeconomic and environmental factors. We have also performed disease mapping of standardized mortality ratios to detect clusters of municipalities with high risk. Further standardization by levels of calcium and magnesium in drinking water shows changes in the maps when we remove the effect of these covariates.

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BACKGROUND: Soft tissue sarcomas of the trunk wall (STS-TW) are usually studied together with soft tissue sarcomas of other locations. We report a study on STS-TW forming part of the French Sarcoma Group database. PATIENTS AND METHODS: Three hundred and forty-three adults were included. We carried out univariate and multivariate analysis for overall survival (OS), metastasis-free survival (MFS) and local recurrence-free survival (LRFS). RESULTS: Tumor locations were as follows: thoracic wall, 82.5%; abdominal wall, 12.3% and pelvic wall, 5.2%. Median tumor size was 6.0 cm. The most frequent tumor types were unclassified sarcoma (27.7%) and myogenic sarcoma (19.2%). A total of 44.6% of cases were grade 3. In all, 21.9% of patients had a previous medical history of radiotherapy (PHR). Median follow-up was 7.6 years. The 5-year OS, MFS and LRFS rates were 60.4%, 68.9% and 58.4%, respectively. Multivariate analysis retained PHR and grade for predicting LRFS and PHR, size and grade as prognostic factors of MFS. Factors influencing OS were age, size, PHR, depth, grade and surgical margins. The predictive factors of incomplete response were PHR, size and T3. CONCLUSIONS: Our results suggest similar classical prognostic factors as compared with sarcomas of other locations. However, a separate analysis of STS-TW revealed a significant poor prognosis subgroup of patients with PHR.

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Despite recent medical progresses in patient support, the mortality of sepsis remains high. Recently, new supporting strategies were proposed to improve outcome. Whereas such strategies are currently considered as standard of care, their real impact on mortality, morbidity, length of stay, and hence, health care resources utilization has been only weakly evaluated so far. Obviously, there is a critical need for epidemiologic surveys of sepsis to better address these major issues. The Lausanne Cohort of septic patients aims at building a large clinical, biological and microbiological database that will be used as a multidisciplinary research platform to study the various pathogenic mechanisms of sepsis in collaboration with the various specialists. This could be an opportunity to strengthen the collaboration within the Swiss Latin network of Intensive Care Medicine.

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PURPOSE: To predict the risk of an adolescent patient to miss an appointment, based on the previous appointments and on the characteristics of the patient and the appointment. METHODS: Two thousand one hundred ninety-three (1873 females) patients aged 12 to 20 years having scheduled at least four appointments were included. We assessed the rate of missed nonexcused appointments of each patient. Second, a Markovian multilevel model was used to predict the risk of defaulting. RESULTS: Forty-five percent of the patients have not missed even once, and 14% of females and 17% of males have missed &gt;25% of their appointments. Females show two types of behaviors (an abstract concept that groups individuals based on a combination of their appointment-keeping and their recorded type of healthcare need) depending on the diagnosis. Somatic, gynecology, violence, and counseling diagnoses are mostly grouped together. In this group, having already missed and having an appointment with a paramedical provider increases the risk of missing. In the second group (eating disorders and psychiatric diagnoses) having already missed and a longer delay between appointments influence the risk of missing, although the risk is lower for this latter group. Males only show one type of behavior regarding missed appointments. Having missed a previous appointment, being older, having cancelled the next to last appointment and the type of diagnosis explain the risk of missing. CONCLUSIONS: Patients who have already defaulted have a higher risk of defaulting again. Means of control regarding missed appointments should consequently focus on defaulters, to decrease the associated workload. Reminders could be a solution for the follow-up appointments scheduled with a long delay.

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BACKGROUND: Renal failure after thoracoabdominal aortic repair is a significant clinical problem. Distal aortic perfusion for organ and spinal cord protection requires cannulation of the left femoral artery. In 2006, we reported the finding that direct cannulation led to leg ischemia in some patients and was associated with increased renal failure. After this finding, we modified our perfusion technique to eliminate leg ischemia from cannulation. In this article, we present the effects of this change on postoperative renal function. METHODS: Between February 1991 and July 2008, we repaired 1464 thoracoabdominal aortic aneurysms. Distal aortic perfusion was used in 1088, and these were studied. Median patient age was 68 years, and 378 (35%) were women. In September 2006, we began to adopt a sidearm femoral cannulation technique that provides distal aortic perfusion while maintaining downstream flow to the leg. This was used in 167 patients (15%). We measured the joint effects of preoperative glomerular filtration rate (GFR) and cannulation technique on the highest postoperative creatinine level, postoperative renal failure, and death. Analysis was by multiple linear or logistic regression with interaction. RESULTS: The preoperative GFR was the strongest predictor of postoperative renal dysfunction and death. No significant main effects of sidearm cannulation were noted. For peak creatinine level and postoperative renal failure, however, strong interactions between preoperative GFR and sidearm cannulation were present, resulting in reductions of postoperative renal complications of 15% to 20% when GFR was <60 mL>/min/1.73 m(2). For normal GFR, the effect was negated or even reversed at very high levels of GFR. Mortality, although not significantly affected by sidearm cannulation, showed a similar trend to the renal outcomes. CONCLUSION: Use of sidearm cannulation is associated with a clinically important and highly statistically significant reduction in postoperative renal complications in patients with a low GFR. Reduced renal effect of skeletal muscle ischemia is the proposed mechanism. Effects among patients with good preoperative renal function are less clear. A randomized trial is needed.

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Introduction: Among the inflammatory mediators involved in the pathogenesis of obesity, the cell adhesion molecules P-selectin, E-selectin, VCAM-1, ICAM-1 and the chemokine MCP-1 stand out. They play a crucial role in adherence of cells to endothelial surfaces, in the integrity of the vascular wall and can be modulated by body composition and dietary pattern. Objectives: To describe and discuss the relation of these cell adhesion molecules and chemokines to anthropometric, body composition, dietary and biochemical markers. Methods: Papers were located using scientific databases by topic searches with no restriction on year of publication. Results: All molecules were associated positively with anthropometric markers, but controversial results were found for ICAM-1 and VCAM-1. Not only obesity, but visceral fat is more strongly correlated with E-selectin and MCP-1 levels. Weight loss influences the reduction in the levels of these molecules, except VCAM-1. The distribution of macronutrients, excessive consumption of saturated and trans fat and a Western dietary pattern are associated with increased levels. The opposite could be observed with supplementation of w-3 fatty acid, healthy dietary pattern, high calcium diet and high dairy intake. Regarding the biochemical parameters, they have inverse relation to HDLC and positive relation to total cholesterol, triglycerides, blood glucose, fasting insulin and insulin resistance. Conclusion: Normal anthropometric indicators, body composition, biochemical parameters and eating pattern positively modulate the subclinical inflammation that results from obesity by reducing the cell adhesion molecules and chemokines.

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Expert curation and complete collection of mutations in genes that affect human health is essential for proper genetic healthcare and research. Expert curation is given by the curators of gene-specific mutation databases or locus-specific databases (LSDBs). While there are over 700 such databases, they vary in their content, completeness, time available for curation, and the expertise of the curator. Curation and LSDBs have been discussed, written about, and protocols have been provided for over 10 years, but there have been no formal recommendations for the ideal form of these entities. This work initiates a discussion on this topic to assist future efforts in human genetics. Further discussion is welcome.

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This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

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Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

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Geographic Information Systems are developed to handle enormous volumes of data and are equipped with numerous functionalities intended to capture, store, edit, organise, process and analyse or represent the geographically referenced information. On the other hand, industrial simulators for driver training are real-time applications that require a virtual environment, either geospecific, geogeneric or a combination of the two, over which the simulation programs will be run. In the final instance, this environment constitutes a geographic location with its specific characteristics of geometry, appearance, functionality, topography, etc. The set of elements that enables the virtual simulation environment to be created and in which the simulator user can move, is usually called the Visual Database (VDB). The main idea behind the work being developed approaches a topic that is of major interest in the field of industrial training simulators, which is the problem of analysing, structuring and describing the virtual environments to be used in large driving simulators. This paper sets out a methodology that uses the capabilities and benefits of Geographic Information Systems for organising, optimising and managing the visual Database of the simulator and for generally enhancing the quality and performance of the simulator.