952 resultados para information criteria
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O prognóstico da perda dentária é um dos principais problemas na prática clínica de medicina dentária. Um dos principais fatores prognósticos é a quantidade de suporte ósseo do dente, definido pela área da superfície radicular dentária intraóssea. A estimação desta grandeza tem sido realizada por diferentes metodologias de investigação com resultados heterogéneos. Neste trabalho utilizamos o método da planimetria com microtomografia para calcular a área da superfície radicular (ASR) de uma amostra de cinco dentes segundos pré-molares inferiores obtida da população portuguesa, com o objetivo final de criar um modelo estatístico para estimar a área de superfície radicular intraóssea a partir de indicadores clínicos da perda óssea. Por fim propomos um método para aplicar os resultados na prática. Os dados referentes à área da superfície radicular, comprimento total do dente (CT) e dimensão mésio-distal máxima da coroa (MDeq) serviram para estabelecer as relações estatísticas entre variáveis e definir uma distribuição normal multivariada. Por fim foi criada uma amostra de 37 observações simuladas a partir da distribuição normal multivariada definida e estatisticamente idênticas aos dados da amostra de cinco dentes. Foram ajustados cinco modelos lineares generalizados aos dados simulados. O modelo estatístico foi selecionado segundo os critérios de ajustamento, preditibilidade, potência estatística, acurácia dos parâmetros e da perda de informação, e validado pela análise gráfica de resíduos. Apoiados nos resultados propomos um método em três fases para estimação área de superfície radicular perdida/remanescente. Na primeira fase usamos o modelo estatístico para estimar a área de superfície radicular, na segunda estimamos a proporção (decis) de raiz intraóssea usando uma régua de Schei adaptada e na terceira multiplicamos o valor obtido na primeira fase por um coeficiente que representa a proporção de raiz perdida (ASRp) ou da raiz remanescente (ASRr) para o decil estimado na segunda fase. O ponto forte deste estudo foi a aplicação de metodologia estatística validada para operacionalizar dados clínicos na estimação de suporte ósseo perdido. Como pontos fracos consideramos a aplicação destes resultados apenas aos segundos pré-molares mandibulares e a falta de validação clínica.
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Introducción Los sistemas de puntuación para predicción se han desarrollado para medir la severidad de la enfermedad y el pronóstico de los pacientes en la unidad de cuidados intensivos. Estas medidas son útiles para la toma de decisiones clínicas, la estandarización de la investigación, y la comparación de la calidad de la atención al paciente crítico. Materiales y métodos Estudio de tipo observacional analítico de cohorte en el que reviso las historias clínicas de 283 pacientes oncológicos admitidos a la unidad de cuidados intensivos (UCI) durante enero de 2014 a enero de 2016 y a quienes se les estimo la probabilidad de mortalidad con los puntajes pronósticos APACHE IV y MPM II, se realizó regresión logística con las variables predictoras con las que se derivaron cada uno de los modelos es sus estudios originales y se determinó la calibración, la discriminación y se calcularon los criterios de información Akaike AIC y Bayesiano BIC. Resultados En la evaluación de desempeño de los puntajes pronósticos APACHE IV mostro mayor capacidad de predicción (AUC = 0,95) en comparación con MPM II (AUC = 0,78), los dos modelos mostraron calibración adecuada con estadístico de Hosmer y Lemeshow para APACHE IV (p = 0,39) y para MPM II (p = 0,99). El ∆ BIC es de 2,9 que muestra evidencia positiva en contra de APACHE IV. Se reporta el estadístico AIC siendo menor para APACHE IV lo que indica que es el modelo con mejor ajuste a los datos. Conclusiones APACHE IV tiene un buen desempeño en la predicción de mortalidad de pacientes críticamente enfermos, incluyendo pacientes oncológicos. Por lo tanto se trata de una herramienta útil para el clínico en su labor diaria, al permitirle distinguir los pacientes con alta probabilidad de mortalidad.
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Ecosystem based management requires the integration of various types of assessment indicators. Understanding stakeholders' information preferences is important, in selecting those indicators that best support management and policy. Both the preferences of decision-makers and the general public may matter, in democratic participatory management institutions. This paper presents a multi-criteria analysis aimed at quantifying the relative importance to these groups of economic, ecological and socio-economic indicators usually considered when managing ecosystem services in a coastal development context. The Analytic Hierarchy Process (AHP) is applied within two nationwide surveys in Australia, and preferences of both the general public and decision-makers for these indicators are elicited and compared. Results show that, on average across both groups, the priority in assessing a generic coastal development project is for the ecological assessment of its impacts on marine biodiversity. Ecological assessment indicators are globally preferred to both economic and socio-economic indicators regardless of the nature of the impacts studied. These results are observed for a significantly larger proportion of decision-maker than general public respondents, questioning the extent to which the general public's preferences are well reflected in decision-making processes.
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We consider two celebrated criteria for defining the nonclassicality of bipartite bosonic quantum systems, the first stemming from information theoretic concepts and the second from physical constraints on the quantum phase space. Consequently, two sets of allegedly classical states are singled out: (i) the set C composed of the so-called classical-classical (CC) states—separable states that are locally distinguishable and do not possess quantum discord; (ii) the set P of states endowed with a positive P representation (P-classical states)—mixtures of Glauber coherent states that, e.g., fail to show negativity of their Wigner function. By showing that C and P are almost disjoint, we prove that the two defining criteria are maximally inequivalent. Thus, the notions of classicality that they put forward are radically different. In particular, generic CC states show quantumness in their P representation, and vice versa, almost all P-classical states have positive quantum discord and, hence, are not CC. This inequivalence is further elucidated considering different applications of P-classical and CC states. Our results suggest that there are other quantum correlations in nature than those revealed by entanglement and quantum discord.
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BACKGROUND: Many users search the Internet for answers to health questions. Complementary and alternative medicine (CAM) is a particularly common search topic. Because many CAM therapies do not require a clinician's prescription, false or misleading CAM information may be more dangerous than information about traditional therapies. Many quality criteria have been suggested to filter out potentially harmful online health information. However, assessing the accuracy of CAM information is uniquely challenging since CAM is generally not supported by conventional literature. OBJECTIVE: The purpose of this study is to determine whether domain-independent technical quality criteria can identify potentially harmful online CAM content. METHODS: We analyzed 150 Web sites retrieved from a search for the three most popular herbs: ginseng, ginkgo and St. John's wort and their purported uses on the ten most commonly used search engines. The presence of technical quality criteria as well as potentially harmful statements (commissions) and vital information that should have been mentioned (omissions) was recorded. RESULTS: Thirty-eight sites (25%) contained statements that could lead to direct physical harm if acted upon. One hundred forty five sites (97%) had omitted information. We found no relationship between technical quality criteria and potentially harmful information. CONCLUSIONS: Current technical quality criteria do not identify potentially harmful CAM information online. Consumers should be warned to use other means of validation or to trust only known sites. Quality criteria that consider the uniqueness of CAM must be developed and validated.
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Federal Highway Administration, Office of Research, Washington, D.C.
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In this paper is proposed a model for researching the capability to influence, by selected methods’ groups of compression, to the co-efficient of information security of selected objects’ groups, exposed to selected attacks’ groups. With the help of methods for multi-criteria evaluation are chosen the methods’ groups with the lowest risk with respect to the information security. Recommendations for future investigations are proposed.
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Research and innovation in the built environment is increasingly taking on an inter-disciplinary nature. The built environment industry and professional practice have long adopted multi and inter-disciplinary practices. The application of IT in Construction is moving beyond the automation and replication of discrete mono and multi-disciplinary tasks to replicate and model the improved inter-disciplinary processes of modern design and construction practice. A major long-term research project underway at the University of Salford seeks to develop IT modelling capability to support the design of buildings and facilities that are buildable, maintainable, operable, sustainable, accessible, and have properties of acoustic, thermal and business support performance that are of a high standard. Such an IT modelling tool has been the dream of the research community for a long time. Recent advances in technology are beginning to make such a modelling tool feasible.----- Some of the key problems with its further research and development, and with its ultimate implementation, will be the challenges of multiple research and built environment stakeholders sharing a common vision, language and sense of trust. This paper explores these challenges as a set of research issues that underpin the development of appropriate technology to support realisable advances in construction process improvements.
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This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.