992 resultados para CLASSIFICATION CRITERIA
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OBJECTIVE To analyze the usability of Computerized Nursing Process (CNP) from the ICNP® 1.0 in Intensive Care Units in accordance with the criteria established by the standards of the International Organization for Standardization and the Brazilian Association of Technical Standards of systems. METHOD This is a before-and-after semi-experimental quantitative study, with a sample of 34 participants (nurses, professors and systems programmers), carried out in three Intensive Care Units. RESULTS The evaluated criteria (use, content and interface) showed that CNP has usability criteria, as it integrates a logical data structure, clinical assessment, diagnostics and nursing interventions. CONCLUSION The CNP is a source of information and knowledge that provide nurses with new ways of learning in intensive care, for it is a place that provides complete, comprehensive, and detailed content, supported by current and relevant data and scientific research information for Nursing practices.
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The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.
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AbstractOBJECTIVETo describe the pressure ulcer healing process in critically ill patients treated with conventional dressing therapy plus low-intensity laser therapy evaluated by the Pressure Ulcer Scale for Healing (PUSH) and the result of Wound Healing: Secondary Intention, according to the Nursing Outcomes Classification (NOC).METHODCase report study according to nursing process conducted with an Intensive Care Unit patient. Data were collected with an instrument containing the PUSH and the result of the NOC. In the analysis we used descriptive statistics, considering the scores obtained on the instrument.RESULTSA reduction in the size of lesions of 7cm to 1.5cm of length and 6cm to 1.1cm width, in addition to the increase of epithelial tissue and granulation, decreased secretion and odor.CONCLUSIONThere was improvement in the healing process of the lesion treated with adjuvant therapy and the use of NOC allowed a more detailed and accurate assessment than the PUSH.
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Abstract OBJECTIVE To assess the nursing workload (NW) in Semi-intensive Therapy Unit, specialized in the care of children with Craniofacial anomalies and associated syndromes; to compare the amount of workforce required according to the Nursing Activities Score (NAS) and the COFEN Resolution 293/04. METHOD Cross-sectional study, whose sample was composed of 72 patients. Nursing workload was assessed through retrospective application of the NAS. RESULTS the NAS mean was 49.5%. Nursing workload for the last day of hospitalization was lower in patients being discharged to home (p<0.001) and higher on the first compared to last day of hospitalization (p< 0.001). The number of professionals required according to NAS was superior to the COFEN Resolution 293/04, being 17 and 14, respectively. CONCLUSION the nursing workload corresponded to approximately 50% of the working time of nursing professional and was influenced by day and outcome of hospitalization. The amount of professionals was greater than that determined by the existing legislation.
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Obesity is recognised as a global epidemic and the most prevalent metabolic disease world-wide. Specialised obesity services, however, are not widely available in Europe, and obesity care can vary enormously across European regions. The European Association for the Study of Obesity (EASO, www.easo.org) has developed these criteria to form a pan-European network of accredited EASO-Collaborating Centres for Obesity Management (EASO-COMs) in accordance with accepted European and academic guidelines. This network will include university, public and private clinics and will ensure that the obese and overweight patient is managed by a holistic team of specialists and receives comprehensive state-ofthe-art clinical care. Furthermore, the participating centres, under the umbrella of EASO, will work closely for quality control, data collection, and analysis as well as for education and research for the advancement of obesity care and obesity science.
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The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.
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Dealing at patient's home with an acute abdominal pain may be particularly challenging for the primary care physician. In such a clinical situation, the part of laboratory and radiological investigations is increasing in the diagnostic process. The decision to keep the patient at home based on a clinical evaluation alone may represent a great medical responsibility for the physician. Emergency departments (ED) are of course in charge of investigating such patients with a wide panel of investigation techniques. But these structures are chronically overcrowded resulting frequently in long and difficult periods of waiting. Based on a literature review, a description of useful clinical symptoms and signs is summarized and should help the decision process for the orientation of the patient.
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BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.
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This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.
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Introduction: Quantitative measures of degree of lumbar spinal stenosis (LSS) such as antero-posterior diameter of the canal or dural sac cross sectional area vary widely and do not correlate with clinical symptoms or results of surgical decompression. In an effort to improve quantification of stenosis we have developed a grading system based on the morphology of the dural sac and its contents as seen on T2 axial images. The grading comprises seven categories ranging form normal to the most severe stenosis and takes into account the ratio of rootlet/CSF content. Material and methods: Fifty T2 axial MRI images taken at disc level from twenty seven symptomatic lumbar spinal stenosis patients who underwent decompressive surgery were classified into seven categories by five observers and reclassified 2 weeks later by the same investigators. Intra- and inter-observer reliability of the classification were assessed using Cohen's and Fleiss' kappa statistics, respectively. Results: Generally, the morphology grading system itself was well adopted by the observers. Its success in application is strongly influenced by the identification of the dural sac. The average intraobserver Cohen's kappa was 0.53 ± 0.2. The inter-observer Fleiss' kappa was 0.38 ± 0.02 in the first rating and 0.3 ± 0.03 in the second rating repeated after two weeks. Discussion: In this attempt, the teaching of the observers was limited to an introduction to the general idea of the morphology grading system and one example MRI image per category. The identification of the dimension of the dural sac may be a difficult issue in absence of complete T1 T2 MRI image series as it was the case here. The similarity of the CSF to possibly present fat on T2 images was the main reason of mismatch in the assignment of the cases to a category. The Fleiss correlation factors of the five observers are fair and the proposed morphology grading system is promising.
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This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.
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In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.
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A singularidade de certos registos geológicos impressos em rochas, as peculiaridades estruturais e dinâmicas dos diversos elementos dos geossistemas, a análise dos seus valores intrínsecos, bem como da sua vulnerabilidade e dos perigos de degradação que os podem afectar, entre outros parâmetros, são factores que concorrem para a necessidade de assegurar a conservação do património geológico. É neste contexto que surge a geoconservação que preconiza a gestão do património geológico com base num conjunto de medidas e acções para a identificação, manutenção ou recuperação do valor natural dos elementos da geodiversidade numa perspectiva de sustentabilidade dos recursos geológicos que integram a componente abiótica do sistema natural. A geoconservação, à escala internacional, tem um desenvolvimento irregular. Enquanto algumas regiões estão bastante avançadas, como na Europa, outras revelam ainda alguma inércia relativamente à implementação de iniciativas que se devem enquadrar no âmbito da conservação da Natureza e do ordenamento do território. Em África, são ainda pontuais os exemplos de geoconservação pelo que, este trabalho, pretende ser promotor de uma política de geoconservação neste continente. No presente trabalho, concebemos uma estratégia de geoconservação para Cabo Verde e aplicamo-la, a título de exemplo, à ilha de Santiago. A metodologia utilizada, baseada em critérios internacionalmente reconhecidos e aceites para o inventário do património geológico de valor científico, consiste no estabelecimento de “categorias temáticas” que representam as características e evolução geológica do arquipélago. Foram propostas nove categorias para Cabo Verde e, para cada uma delas, foram inventariados diversos locais de interesse, dos quais 40 foram propostos como geossítios na ilha de Santiago. Com base nestes geossítios, propuseram-se linhas metodológicas para as etapas subsequentes que integram uma estratégia de geoconservação, nomeadamente, a quantificação, classificação, conservação, valorização, divulgação e monitorização de geossítios. Embora a conservação da geodiversidade esteja prevista, embora de forma pouco clara, na actual legislação ambiental cabo-verdiana, a execução desta estratégia de geoconservação poderá representar um dos primeiros passos para a definição, caracterização e valorização, sistemáticas, do património geológico nacional e contribuir para a implementação de uma política de sustentabilidade ambiental para o país.