870 resultados para International Classification of Diseases


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A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

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Background and Aims: To protect the population from environmental tobacco smoke (ETS) Switzerland introduced a nationwide rather heterogeneous smoking ban in May 2010. The exposure situation of non-smoking hospitality workers before and after implementation of the new law is being assessed in a prospective cohort study. Methods: Exposure to ETS was measured using a novel method developed by the Institute for Work and Health in Lausanne. It is a passive sampler called MoNIC (Monitor of NICotine). The nicotine of the ETS is fixed onto a filter and transformed into salt of not volatile nicotine. Subsequently the number of passively smoked cigarettes is calculated. Badges were placed at the workplace as well as distributed to the participants for personal measuring. Additionally a salivary sample was taken to determine nicotine concentration. Results: At baseline Spearman's correlation between workplace and personal badge was 0.47. The average cigarette equivalents per day at the workplace obtained by badge significantly dropped from 5.1 (95%- CI: 2.4 to 7.9) at baseline to 0.3 (0.2 to 0.4) at first follow-up (n=29) three months later (p<0.001). For personal badges the number of passively smoked cigarettes declined from 1.5 (2.7 to 0.4) per day to 0.5 (0.3 to 0.8) (n=16).Salivary nicotine concentration in a subset of 13 participants who had worked on the day prior to the examination was 2.63 ng/ml before and 1.53 ng/ml after the ban (p=0.04). Spearman's correlation of salivary nicotine was 0.56 with workplace badge and 0.79 with personal badge concentrations. Conclusions: Workplace measurements clearly reflect the smoking regulation in a venue. The MoNIC badge proves to be a sensitive measuring device to determine personal ETS exposure and it is a demonstrative measure for communication with lay audiences and study participants as the number of passively smoked cigarettes is an easily conceivable result.

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In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

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A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

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Protein energy wasting (PEW) is common in patients with chronic kidney disease (CKD) and is associated with adverse clinical outcomes, especially in individuals receiving maintenance dialysis therapy. A multitude of factors can affect the nutritional and metabolic status of CKD patients requiring a combination of therapeutic maneuvers to prevent or reverse protein and energy depletion. These include optimizing dietary nutrient intake, appropriate treatment of metabolic disturbances such as metabolic acidosis, systemic inflammation, and hormonal deficiencies, and prescribing optimized dialytic regimens. In patients where oral dietary intake from regular meals cannot maintain adequate nutritional status, nutritional supplementation, administered orally, enterally, or parenterally, is shown to be effective in replenishing protein and energy stores. In clinical practice, the advantages of oral nutritional supplements include proven efficacy, safety, and compliance. Anabolic strategies such as anabolic steroids, growth hormone, and exercise, in combination with nutritional supplementation or alone, have been shown to improve protein stores and represent potential additional approaches for the treatment of PEW. Appetite stimulants, anti-inflammatory interventions, and newer anabolic agents are emerging as novel therapies. While numerous epidemiological data suggest that an improvement in biomarkers of nutritional status is associated with improved survival, there are no large randomized clinical trials that have tested the effectiveness of nutritional interventions on mortality and morbidity.

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To classify mosquito species based on common features of their habitats, samples were obtained fortnightly between June 2001-October 2003 in the subtropical province of Chaco, Argentina. Data on the type of larval habitat, nature of the habitat (artificial or natural), size, depth, location related to sunlight, distance to the neighbouring houses, type of substrate, organic material, vegetation and algae type and their presence were collected. Data on the permanence, temperature, pH, turbidity, colour, odour and movement of the larval habitat's water were also collected. From the cluster analysis, three groups of species associated by their degree of habitat similarity were obtained and are listed below. Group 1 consisted of Aedes aegypti. Group 2 consisted of Culex imitator, Culex davisi, Wyeomyia muehlensi and Toxorhynchites haemorrhoidalis separatus. Within group 3, two subgroups are distinguished: A (Psorophora ferox, Psorophora cyanescens, Psorophora varinervis, Psorophora confinnis, Psorophora cingulata, Ochlerotatus hastatus-oligopistus, Ochlerotatus serratus, Ochlerotatus scapularis, Culex intrincatus, Culex quinquefasciatus, Culex pilosus, Ochlerotatus albifasciatus, Culex bidens) and B (Culex maxi, Culex eduardoi, Culex chidesteri, Uranotaenia lowii, Uranotaenia pulcherrima, Anopheles neomaculipalpus, Anopheles triannulatus, Anopheles albitarsis, Uranotaenia apicalis, Mansonia humeralis and Aedeomyia squamipennis). Principal component analysis indicates that the size of the larval habitats and the presence of aquatic vegetation are the main characteristics that explain the variation among different species. In contrast, water permanence is second in importance. Water temperature, pH and the type of larval habitat are less important in explaining the clustering of species.

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BACKGROUND: Extension of retinoblastoma cells into the posterior chamber is a criterion for group E according to the international classification of intraocular retinoblastoma. Currently, the anterior extension of retinoblastoma is based on the presence of tumour cells in the anterior chamber assessed by biomicroscopy. AIM: To determine the value of ultrasound biomicroscopy (UBM) in the assessment of posterior chamber involvement in advanced retinoblastoma. METHODS: Retrospective review of all retinoblastoma cases enucleated at the Jules Gonin Eye Hospital from January 1996 to December 2009 for which UBM (35 MHz) evaluation was available. The patients' records were reviewed for patient and tumour features and histopathological findings. UBM findings were compared with histopathological features. RESULTS: UBM documentation was available in 31 cases. Retinoblastoma was detected by UBM in the posterior chamber in 18 cases and was absent in 13 cases while histopathological analysis demonstrated its presence in the posterior chamber in 22 cases and its absence in 9 cases. Among the 18 UBM-positive cases, 7 had biomicroscopic detectable involvement of the anterior chamber. There was a significant correlation between echodensities consistent with retinoblastoma on UBM in the posterior chamber and histopathological tumorous involvement of the posterior chamber (p=0.0001). The sensitivity of UBM in the assessment of posterior chamber invasion by retinoblastoma was 81% and the specificity was 100%. CONCLUSION: In selected cases of advanced retinoblastoma, UBM appears to represent a valuable tool in the precise evaluation of anterior extension of disease, with good sensitivity and specificity for the assessment of posterior chamber involvement. UBM may provide useful criteria governing the indication for enucleation.

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The use of chemical insecticides continues to play a major role in the control of disease vector populations, which is leading to the global dissemination of insecticide resistance. A greater capacity to detoxify insecticides, due to an increase in the expression or activity of three major enzyme families, also known as metabolic resistance, is one major resistance mechanisms. The esterase family of enzymes hydrolyse ester bonds, which are present in a wide range of insecticides; therefore, these enzymes may be involved in resistance to the main chemicals employed in control programs. Historically, insecticide resistance has driven research on insect esterases and schemes for their classification. Currently, several different nomenclatures are used to describe the esterases of distinct species and a universal standard classification does not exist. The esterase gene family appears to be rapidly evolving and each insect species has a unique complement of detoxification genes with only a few orthologues across species. The examples listed in this review cover different aspects of their biochemical nature. However, they do not appear to contribute to reliably distinguish among the different resistance mechanisms. Presently, the phylogenetic criterion appears to be the best one for esterase classification. Joint genomic, biochemical and microarray studies will help unravel the classification of this complex gene family.

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In 2009, the World Health Organization (WHO) issued a new guideline that stratifies dengue-affected patients into severe (SD) and non-severe dengue (NSD) (with or without warning signs). To evaluate the new recommendations, we completed a retrospective cross-sectional study of the dengue haemorrhagic fever (DHF) cases reported during an outbreak in 2011 in northeastern Brazil. We investigated 84 suspected DHF patients, including 45 (53.6%) males and 39 (46.4%) females. The ages of the patients ranged from five-83 years and the median age was 29. According to the DHF/dengue shock syndrome classification, 53 (63.1%) patients were classified as having dengue fever and 31 (36.9%) as having DHF. According to the 2009 WHO classification, 32 (38.1%) patients were grouped as having NSD [4 (4.8%) without warning signs and 28 (33.3%) with warning signs] and 52 (61.9%) as having SD. A better performance of the revised classification in the detection of severe clinical manifestations allows for an improved detection of patients with SD and may reduce deaths. The revised classification will not only facilitate effective screening and patient management, but will also enable the collection of standardised surveillance data for future epidemiological and clinical studies.

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A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours

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It has been suggested that converting, via a process of cross-coding, the listing used by the Swiss Disability Insurance (SDI) for their statistics into codes of the International Classification of Impairments, Disabilities, and Handicaps (ICIDH) would improve the quality and international comparability of disability statistics for Switzerland. Using two different methods we tested the feasibility of this cross-coding on a consecutive sample of 204 insured persons, examined at one of the medical observation centres of the SDI. Cross-coding is impossible, for all practical purposes, in a proportion varying between 30% and 100%, depending on the method of cross-coding, the level of disablement and the required quality of the resulting codes. Failure is due to lack of validity of the SDI codes: diseases are poorly described, consequences of diseases (disability and handicap, including loss of earning capacity), insufficiently described or not at all. Assessment of disability and handicap would provide necessary information for the SDI. It is concluded that the SDI should promote the use of the ICIDH in Switzerland, especially among medical practitioners whose assessment of work capacity is the key element in the decision to award benefits or propose rehabilitation.

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The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.