987 resultados para Decision-Maker


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ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

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We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

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ABSTRACT: BACKGROUND: Shared decision-making is not widely implemented in healthcare. We aimed to set a research agenda about promoting shared decision-making through continuing professional development. METHODS: Thirty-six participants met for two days. RESULTS: Participants suggested ways to improve an environmental scan that had inventoried 53 shared decision-making training programs from 14 countries. Their proposed research agenda included reaching an international consensus on shared decision-making competencies and creating a framework for accrediting continuing professional development initiatives in shared decision-making. CONCLUSIONS: Variability in shared decision-making training programs showcases the need for quality assurance frameworks.

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Abstract¿La deteción del espectro libre para las comunicaciones inalámbricas en un momento puntual es una tarea compleja cuyo desarrollo se simplica al realizarse de forma distribuida por una red de radio cognitiva. Sin embargo existes dificultades y vulnerabilidades de seguridad que han de ser tenidas en cuenta y solventadas a la hora de autenticar y validar los nodos de la red. Este artículo presenta una propuesta de mejora del protocolo fully distributed decision making protocol for CRN con el fin de llevar a cabo esta tarea de detección del espectro de una manera eficiente y segura.

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Este artículo presenta una propuesta de mejora del protocolo fully distributed decision making protocol for CRN con el fin de llevar a cabo la tarea de detección del espectro libre para las comunicaciones inalámbricas de una manera eficiente y segura.

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Background: Cardiac magnetic resonance (CMR) is accepted as a method to assess suspected coronary artery disease (CAD). Nonetheless, invasive coronary angiography (CXA) combined or not with fractional flow reserve (FFR) remains the main diagnostic test to evaluate CAD. Little data exist on the economic impact of the use of these procedures in a population with a low to intermediate pre-test probability. Objective: To compare the costs of 3 decision strategies to revascularize a patient with suspected CAD: 1) strategy guided by CMR 2) hypothetical strategy guided by CXA-FFR, 3) hypothetical strategy guided by CXA alone.

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Auditors face the difficult responsibilty to approve companies' financial accounting information reliably. They are trained to work according to accounting standards that are designed to help them in their decision making. Yet, auditors do not work in a social vacuum and are thus subject to various influences. One important source of influence at work is authority figures (e.g., experts, supervisors). On this background, we examined within two studies the impact of (1) authority advice to comply with accounting standards or to additionally maximize profits and (2) of participants' accountability for their decision. In Study 1, (n = 184 accounting students), participants who were advised by an authority to comply with accounting standards had a lower probability to recognise transactions that violated those standards than participants who were advised to comply but also to maximise profit. However, holding participants accountable for their decision reduced the difference between the two groups. In Study 2, (n = 58 managers), we again found an interaction between authority advice and accountability. But unlike the first study, participants only showed a lower probability to recognise transactions that violated accounting standards when they were held accountable and when the authority only advised them to comply with the standards. We discuss our results in light of unethical decision making and different norms or pressures to which managers may be exposed but students may not.

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At a time when disciplined inference and decision making under uncertainty represent common aims to participants in legal proceedings, the scientific community is remarkably heterogenous in its attitudes as to how these goals ought to be achieved. Probability and decision theory exert a considerable influence, and we think by all reason rightly do so, but they go against a mainstream of thinking that does not embrace-or is not aware of-the 'normative' character of this body of theory. It is normative, in the sense understood in this article, in that it prescribes particular properties, typically (logical) coherence, to which reasoning and decision making ought to conform. Disregarding these properties can result in diverging views which are occasionally used as an argument against the theory, or as a pretext for not following it. Typical examples are objections according to which people, both in everyday life but also individuals involved at various levels in the judicial process, find the theory difficult to understand and to apply. A further objection is that the theory does not reflect how people actually behave. This article aims to point out in what sense these examples misinterpret the analytical framework in its normative perspective. Through examples borrowed mostly from forensic science contexts, it is argued that so-called intuitive scientific attitudes are particularly liable to such misconceptions. These attitudes are contrasted with a statement of the actual liberties and constraints of probability and decision theory and the view according to which this theory is normative.

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Most local agencies in Iowa currently make their pavement treatment decisions based on their limited experience due primarily to lack of a systematic decision-making framework and a decision-aid tool. The lack of objective condition assessment data of agency pavements also contributes to this problem. This study developed a systematic pavement treatment selection framework for local agencies to assist them in selecting the most appropriate treatment and to help justify their maintenance and rehabilitation decisions. The framework is based on an extensive literature review of the various pavement treatment techniques in terms of their technical applicability and limitations, meaningful practices of neighboring states, and the results of a survey of local agencies. The treatment selection framework involves three different steps: pavement condition assessment, selection of technically feasible treatments using decision trees, and selection of the most appropriate treatment considering the return-on-investment (ROI) and other non-economic factors. An Excel-based spreadsheet tool that automates the treatment selection framework was also developed, along with a standalone user guide for the tool. The Pavement Treatment Selection Tool (PTST) for Local Agencies allows users to enter the severity and extent levels of existing distresses and then, recommends a set of technically feasible treatments. The tool also evaluates the ROI of each feasible treatment and, if necessary, it can also evaluate the non-economic value of each treatment option to help determine the most appropriate treatment for the pavement. It is expected that the framework and tool will help local agencies improve their pavement asset management practices significantly and make better economic and defensible decisions on pavement treatment selection.

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Adverse weather conditions dramatically affect the nation’s surface transportation system. The development of a prototype winter Maintenance Decision Support System (MDSS) is part of the Federal Highway Administration’s effort to produce a prototype tool for decision support to winter road maintenance managers to help make the highways safer for the traveling public. The MDSS is based on leading diagnostic and prognostic weather research capabilities and road condition algorithms, which are being developed at national research centers. In 2003, the Iowa Department of Transportation was chosen as a field test bed for the continuing development of this important research program. The Center for Transportation Research and Education assisted the Iowa Department of Transportation by collecting and analyzing surface condition data. The Federal Highway Administration also selected five national research centers to participate in the development of the prototype MDSS. It is anticipated that components of the prototype MDSS system developed by this project will ultimately be deployed by road operating agencies, including state departments of transportation, and generally supplied by private vendors.

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We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

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Which neurons in the brain "decide" to initiate particular behaviors in response to sensory information? In this issue of Neuron, two papers (Kohatsu et al. and von Philipsborn et al.) identify candidates in the courtship circuitry of Drosophila. The activity of these neurons is both regulated by sex pheromones and necessary and sufficient to trigger male love song.

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In decision making, speed-accuracy trade-offs are well known and often inevitable because accuracy depends on being well informed and gathering information takes time. However, trade-offs between speed and cohesion, that is the degree to which a group remains together as a single entity, as a result of their decision making, have been comparatively neglected. We combine theory and experimentation to show that in decision-making systems, speed-cohesion trade-offs are a natural complement to speed-accuracy trade-offs and are therefore of general importance. We then analyse the decision performance of 32 rock ant, Temnothorax albipennis, colonies in experiments in which accuracy of collective decision making was held constant, but time urgency varied. These experiments reveal for the first time an adaptive speed-cohesion trade-off in collective decision making and how this is achieved. In accord with different time constraints, colonies can decide quickly, at the cost of social unity, or they can decide slowly with much greater cohesion. We discuss the similarity between cohesion and the term precision as used in statistics and engineering. This emphasizes the generality of speed versus cohesion/precision trade-offs in decision making and decision implementation in other fields within animal behaviour such as sexually selected motor displays and even certain aspects of birdsong. We also suggest that speed versus precision trade-offs may occur when individuals within a group need to synchronize their activity, and in collective navigation, cooperative hunting and in certain escape behaviours.