9 resultados para predictive value

em Aston University Research Archive


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Background - Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method - GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results - The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions - Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

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This article considers the role of accounting in organisational decision making. It challenges the rational nature of decisions made in organisations through the use of accounting models and the problems of predicting the future through the use of such models. The use of accounting in this manner is evaluated from an epochal postmodern stance. Issues raised by chaos theory and the uncertainty principle are used to demonstrate problems with the predictive ability of accounting models. The authors argue that any consideration of the predictive value of accounting needs to change to incorporate a recognition of the turbulent external environment, if it is to be of use for organisational decision making. Thus it is argued that the role of accounting as a mechanism for knowledge creation regarding the future is fundamentally flawed. We take this as a starting-point to argue for the real purpose of the use of the predictive techniques of accounting, using its ritualistic role in the context of myth creation to argue for the cultural benefits of the use of such flawed techniques.

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Developmental stability is the degree to which we can withstand environmental or genetic stressors during development. Fluctuating asymmetry (FA), concerns the extent to which the right and left side of the body is asymmetrical and is one way to measure developmental stability. Two studies were carried out that examined both the predictive value of leader FA with leadership behaviors and its role in facilitating group performance. The first study examined the hypothesis that a leader's FA is correlated with scores on the Multifactor Leadership Questionnaire (MLQ). The results revealed individuals with a more asymmetrical morphology scored higher on the transformational, but not transactional, dimensions of leadership behavior. A second study examined the hypothesis that asymmetrical morphology and leadership effectiveness would share a positive relationship. In this study participants who led a business game exercise, revealed a positive relationship between FA and self-reported well-being and task satisfaction. Importantly, there was also a positive correlation between the leader's FA score and group performance. The role that developmental stability may play in leadership effectiveness is discussed in the wider context of evolutionary psychology.

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This thesis examines the predictive value of a conceptual distinction between status-seeking associations and status-maintaining associations for enhancing understanding of ten selected professional associations and of the attitudes, values, behaviour and policies of their governing organs. Thirty four specific hypotheses have been tested by such research methods as questionnaires administered to individuals and associations, participant observation and an examination of association minutes and publications. Certain hypotheses have been found to be valid for particular matched pairs and/or groups of associations. The findings of the study suggest that the present conceptualisation of profession, the individual professional, professionalism, professionalisation, professional status and that relating to the role of the professions in society needs to be refined and modified in varying degrees in application to accounting associations, business graduate associations and management associations. The concept of the `ideal type' profession is shown to be of limited value in understanding certain aspects of the activities of business graduate and management associations. The findings of the study suggest that in future the professional associations examined may attach less importance to their qualifying role and lay more stress upon their representational role. The professional association faces a managerial challenge to adjust and adapt to a range of `external' pressures and `internal' demands from members and may increasingly need to be regarded as an organisation that possesses certain combinations or sets of characteristics rather than as a type of organisation that possesses a particular or relatively exclusive set. With a blurring of the distinction between the professional and state sector vocational education, and a growing customer/market orientation associated with the changing nature of work, membership of a professional association may, in future, come to be associated rather more with securing access to a relevant range of services and less with qualification for a particular career.

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Congenital nystagmus is an ocular-motor disorder characterised by involuntary, conjugated and bilateral to and fro ocular oscillations. In this study a method to recognise automatically jerk waveform inside a congenital nystagmus recording and to compute foveation time and foveation position variability is presented. The recordings were performed with subjects looking at visual targets, presented in nine eye gaze positions; data were segmented into blocks corresponding to each gaze position. The nystagmus cycles were identified searching for local minima and maxima (SpEp sequence) in intervals centred on each slope change of the eye position signal (position criterion). The SpEp sequence was then refined using an adaptive threshold applied to the eye velocity signal; the outcome is a robust detection of each slow phase start point, fundamental to accurately compute some nystagmus parameters. A total of 1206 slow phases was used to compute the specificity in waveform recognition applying only the position criterion or adding the adaptive threshold; results showed an increase in negative predictive value of 25.1% using both features. The duration of each foveation window was measured on raw data or using an interpolating function of the congenital nystagmus slow phases; foveation time estimation less sensitive to noise was obtained in the second case. © 2010.

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Because memories are not always accurate, people rely on a variety of strategies to verify whether the events that they remember really did occur. Several studies have examined which strategies people tend to use, but none to date has asked why people opt for certain strategies over others. Here we examined the extent to which people's beliefs about the reliability and the cost of different strategies would determine their strategy selection. Subjects described a childhood memory and then suggested strategies they might use to verify the accuracy of that memory. Next, they rated the reliability and cost of each strategy, and the likelihood that they might use it. Reliability and cost each predicted strategy selection, but a combination of the two ratings provided even greater predictive value. Cost was significantly more influential than reliability, which suggests that a tendency to seek and to value "cheap" information more than reliable information could underlie many real-world memory errors. © 2013 Elsevier B.V.

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Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

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Customer satisfaction and service quality are two important concepts in the marketing literature. However, there has been some confusion about the conceptualisation and measurement of these two concepts and the nature of the relationship between them. The primary objective of this research was to develop a more thorough understanding of these concepts, and a model that could help to explain the links between them and their relationships with post-purchase behaviour. A preliminary theoretical model was developed, based on an exhaustive review of the literature. Following exploratory research, the model was revised by incorporating "Perceived Value" and "Perceived Sacrifice" to help explain customer's post-purchase behaviour. A longitudinal survey was conducted in the context of the restaurant industry, and the data were analysed using structural equation modelling. The results provided evidence to support the main research hypotheses. However, the effect of "Normative Expectations" on "Encounter Quality" was insignificant, and "Perceived Value" had a direct effect on "Behavioural Intentions" despite expectations that such an effect would be mediated through "Customer Satisfaction". It was also found that "Normative Expectations" were relatively more stable than "Predictive Expectations". It is argued that the present research significantly contributes to the marketing literature, and in particular the role of perceived value in the formation of customers' post-purchase behaviour. Further research efforts in this area are warranted.

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Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.