17 resultados para expert opinon

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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PURPOSE: Screening programs to detect visual abnormalities in children vary among countries. The aim of this study is to describe experts' perception of best practice guidelines and competency framework for visual screening in children. METHODS: A qualitative focus group technique was applied during the Portuguese national orthoptic congress to obtain the perception of an expert panel of 5 orthoptists and 2 ophthalmologists with experience in visual screening for children (mean age 53.43 years, SD ± 9.40). The panel received in advance a script with the description of three tuning competencies dimensions (instrumental, systemic, and interpersonal) for visual screening. The session was recorded in video and audio. Qualitative data were analyzed using a categorical technique. RESULTS: According to experts' views, six tests (35.29%) have to be included in a visual screening: distance visual acuity test, cover test, bi-prism or 4/6(Δ) prism, fusion, ocular movements, and refraction. Screening should be performed according to the child age before and after 3 years of age (17.65%). The expert panel highlighted the influence of the professional experience in the application of a screening protocol (23.53%). They also showed concern about the false negatives control (23.53%). Instrumental competencies were the most cited (54.09%), followed by interpersonal (29.51%) and systemic (16.4%). CONCLUSIONS: Orthoptists should have professional experience before starting to apply a screening protocol. False negative results are a concern that has to be more thoroughly investigated. The proposed framework focuses on core competencies highlighted by the expert panel. Competencies programs could be important do develop better screening programs.

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The aim of this study was to describe experts’ perception of best-practice guidelines and competency framework for visual screening in children. This study uses qualitative data and shows individual/ group conceptualization. The use of evidence from qualitative studies has traditionally been a fundamental source of knowledge in the clinical and social sciences.

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Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.

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Screening programs, particularly the inclusion of specific orthoptic tests to detect visual abnormalities, varies among countries. This study aims to: 1) describes expert perception of issues related with children visual screening; 2) identify specific orthoptic tests to detect visual abnormalities in children visual screening.

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Mestrado em Intervenção Sócio-Organizacional na Saúde. Área de especialização: Políticas de Administração e Gestão dos Serviços de Saúde.

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A criação da medida de política educativa (Despacho Normativo n.º 55/2008) - Territórios Educativos de Intervenção Prioritária (TEIP) corresponde à necessidade de concretização de um princípio da Lei de Bases do Sistema Educativo português, visando assegurar uma educação de base para todos, bem sucedida. Esta mesma medida acontece na sequência de uma outra anterior com as mesmas características, criada no ano lectivo de 1996/1997. A sua implementação no terreno foi objecto de um estudo encomendado pelo Instituto de Inovação Educacional no qual participei, integrando uma equipa de investigação da Faculdade de Psicologia e Ciências da Educação da Universidade de Lisboa. Nesta comunicação, proponho-me revisitar esse mesmo estudo, dando conta do balanço crítico então realizado, e, à luz das suas principais conclusões, refletir agora na qualidade de perito externo de um TEIP da região de Lisboa, sobre os modos como os TEIP2 evoluíram, em que sentido se deu tal evolução e quais os problemas que persistem. A consecução de um dos objectivos centrais desta medida de política educativa, especificamente a melhoria da qualidade das aprendizagens traduzida no sucesso educativo dos alunos, parece, de acordo com os relatórios oficiais, não ser ainda muito expressiva nem muito consistente. Torna-se, portanto, necessário interrogar e problematizar as práticas de ensino realizadas pelos professores, repensando estratégias pedagógicas que se configurem relevantes para dar expressão real àquele objectivo.

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PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

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Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

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Beaches worldwide provide recreational opportunities to hundreds of millions of people and serve as important components of coastal economies. Beach water is often monitored for microbiological quality to detect the presence of indicators of human sewage contamination so as to prevent public health outbreaks associated with water contact. However, growing evidence suggests that beach sand can harbor microbes harmful to human health, often in concentrations greater than the beach water. Currently, there are no standards for monitoring, sampling, analyzing, or managing beach sand quality. In addition to indicator microbes, growing evidence has identified pathogenic bacteria, viruses, and fungi in a variety of beach sands worldwide. The public health threat associated with these populations through direct and indirect contact is unknown because so little research has been conducted relating to health outcomes associated with sand quality. In this manuscript, we present the consensus findings of a workshop of experts convened in Lisbon, Portugal to discuss the current state of knowledge on beach sand microbiological quality and to develop suggestions for standardizing the evaluation of sand at coastal beaches. The expert group at the "Microareias 2012" workshop recommends that 1) beach sand should be screened for a variety of pathogens harmful to human health, and sand monitoring should then be initiated alongside regular water monitoring; 2) sampling and analysis protocols should be standardized to allow proper comparisons among beach locations; and 3) further studies are needed to estimate human health risk with exposure to contaminated beach sand. Much of the manuscript is focused on research specific to Portugal, but similar results have been found elsewhere, and the findings have worldwide implications.

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Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

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Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff. © 2014 IEEE.

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The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

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Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.