526 resultados para multi-turn injection
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Background Lumbar Epidural Steroids Injections (ESI’s) have previously been shown to provide some degree of pain relief in sciatica. Number Needed To Treat (NNT) to achieve 50% pain relief has been estimated at 7 from the results of randomised controlled trials. Pain relief is temporary. They remain one of the most commonly provided procedures in the UK. It is unknown whether this pain relief represents good value for money. Methods 228 patients were randomised into a multi-centre Double Blind Randomised Controlled Trial. Subjects received up to 3 ESI’s or intra-spinous saline depending on response and fall off with the first injection. All other treatments were permitted. All received a review of analgesia, education and physical therapy. Quality of life was assessed using the SF36 at 6 points and compared using independent sample t-tests. Follow up was up to 1 yr. Missing data was imputed using last observation carried forward (LOCF). QALY’s (Quality of Life Years) were derived from preference based heath values (summary health utility score). SF-6D health state classification was derived from SF-36 raw score data. Standard gambles (SG) were calculated using Model 10. SG scores were calculated on trial results. LOCF was not used for this. Instead average SG were derived for a subset of patients with observations for all visits up to week 12. Incremental QALY’s were derived as the difference in the area between the SG curve for the active group and placebo group. Results SF36 domains showed a significant improvement in pain at week 3 but this was not sustained (mean 54 Active vs 61 Placebo P<0.05). Other domains did not show any significant gains compared with placebo. For derivation of SG the number in the sample in each period differed. In week 12, average SG scores for active and placebo converged. In other words, the health gain for the active group as measured by SG was achieved by the placebo group by week 12. The incremental QALY gained for a patient under the trial protocol compared with the standard care package was 0.0059350. This is equivalent to an additional 2.2 days of full health. The cost per QALY gained to the provider from a patient management strategy administering one epidural as suggested by results was £25 745.68. This result was derived assuming that the gain in QALY data calculated for patients under the trial protocol would approximate that under a patient management strategy based on the trial results (one ESI). This is above the threshold suggested by some as a cost effective treatment. Conclusions The transient benefit in pain relief afforded by ESI’s does not appear to be cost-effective. Further work is needed to develop more cost-effective conservative treatments for sciatica.
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In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.
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This study was a step forward to improve the performance for discovering useful knowledge – especially, association rules in this study – in databases. The thesis proposed an approach to use granules instead of patterns to represent knowledge implicitly contained in relational databases; and multi-tier structure to interpret association rules in terms of granules. Association mappings were proposed for the construction of multi-tier structure. With these tools, association rules can be quickly assessed and meaningless association rules can be justified according to the association mappings. The experimental results indicated that the proposed approach is promising.
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Karasek's Job Demand-Control model proposes that control mitigates the positive effects of work stressors on employee strain. Evidence to date remains mixed and, although a number of individual-level moderators have been examined, the role of broader, contextual, group factors has been largely overlooked. In this study, the extent to which control buffered or exacerbated the effects of demands on strain at the individual level was hypothesized to be influenced by perceptions of collective efficacy at the group level. Data from 544 employees in Australian organizations, nested within 23 workgroups, revealed significant three-way cross-level interactions among demands, control and collective efficacy on anxiety and job satisfaction. When the group perceived high levels of collective efficacy, high control buffered the negative consequences of high demands on anxiety and satisfaction. Conversely, when the group perceived low levels of collective efficacy, high control exacerbated the negative consequences of high demands on anxiety, but not satisfaction. In addition, a stress-exacerbating effect for high demands on anxiety and satisfaction was found when there was a mismatch between collective efficacy and control (i.e. combined high collective efficacy and low control). These results provide support for the notion that the stressor-strain relationship is moderated by both individual- and group-level factors.
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Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.
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Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.
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Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.
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Dealing with the large amount of data resulting from association rule mining is a big challenge. The essential issue is how to provide efficient methods for summarizing and representing meaningful discovered knowledge from databases. This paper presents a new approach called multi-tier granule mining to improve the performance of association rule mining. Rather than using patterns, it uses granules to represent knowledge that is implicitly contained in relational databases. This approach also uses multi-tier structures and association mappings to interpret association rules in terms of granules. Consequently, association rules can be quickly assessed and meaningless association rules can be justified according to these association mappings. The experimental results indicate that the proposed approach is promising
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In Kumar v Suncorp Metway Insurance Limited [2004] QSC 381 Douglas J examined s37 of the Motor Accident Insurance Act 1994 (Qld) in the context of an accident involving multiple insurers when a notice of accident had not been given to the Nominal Defendant
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This paper strives to identify barriers that hamper eHealth implementation from different perspectives. The benefits offered by eHealth and the need for eHealth preparedness is first discussed. This is followed by a discussion on the integral components of a robust eHealth infrastructure. Then, the barriers to eHealth such as technical interoperability issues, lack of holistic approach and technology disconnect are explained in detail. Finally, solutions to promote better adoption of eHealth through government policies, standardisation and training are also discussed.
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FROM KCWS 2011 CHAIRS AND SUMMIT PROCEEDING EDITORS In recent years, with the impact of global knowledge economy, a more comprehensive development approach has gained significant popularity. This new development approach, so called ‘knowledgebased development’, is different from its traditional predecessor. With a much more balanced focus on all of the four key development domains – economic, enviro-urban, institutional, and sociocultural – this contemporary approach, aims to bring economic prosperity, environmental sustainability and local institutional competence with a just socio-spatial order to our cities and regions. The ultimate goal of knowledge-based development is to produce a city purposefully designed to encourage the continuous production, circulation and commercialisation of social and scientific knowledge – this will in turn establish a ‘knowledge city’. A city following the ‘knowledge city’ concept embarks on a strategic mission to firmly encourage and nurture locally focussed innovation, science and creativity within the context of an expanding knowledge economy and society. In this regard a ‘knowledge city’ can be seen as an integrated city, which physically and institutionally combines the functions of a science and technology park with civic and residential functions and urban amenities. It also offers one of the effective paradigms for the sustainable cities of our time. This fourth edition of KCWS – The 4th Knowledge Cities World Summit 2011 – makes an important reminder that the 'knowledge city' concept is a key notion in the 21st Century development. Considering this notion, the Summit sheds light on the multi-faceted dimensions and various scales of building a ‘knowledge city’ via 'knowledge-based development' paradigm by particularly focusing on the overall Summit theme of ‘Knowledge Cities for Future Generations’. At this summit, the theoretical and practical maturing of knowledge-based development paradigms are advanced through the interplay between the world’s leading academics’ theories and the practical models and strategies of practitioners’ and policy makers’ drawn from around the world. This summit proceeding is compiled in order to disseminate the knowledge generated and shared in KCWS 2011 with the wider research, governance, and practice communities the knowledge cocreated in this summit. All papers of this proceeding have gone through a double-blind peer review process and been reviewed by our summit editorial review and advisory board members. We, organisers of the summit, cordially thank the members of the Summit Proceeding Editorial Review and Advisory Board for their diligent work in the review of the papers. We hope the papers in this proceeding will inspire and make a significant contribution to the research, governance, and practice circles.
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This paper treats one particular version of the multi-utility strategy as experienced by the Hyder Group. We examine some aspectw of the company's financial performance and consider the implications.
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An experiment was conducted to investigate the process of reasoning about directions in an egocentric space. Each participant walked through a corridor containing an angular turn ranging in size from 0° to 90°, in 15° increments. A direction was given to participants at the entrance of the corridor and they were asked to answer this direction at the end of this corridor. Considering the fact that participants had to reason the direction in the featureless corridor, two hypotheses were proposed: (i) reasoning about directions falls into qualitative reasoning by using a small number of coarse angular categories (four 90° categories or eight 45° categories: 90° categories consist of front, back, left, right; 45° categories consist of 90° categories and the four intermediates) that reference axes generate; (ii) reasoning about directions would be done by recalling the rotation angle from the traveling direction to the direction that participants tried to answer. In addition, the configuration of reference axes that participants employed was examined. Both hypotheses were supported, and the data designated that reference axes consisted of eight directions: a pair of orthogonal axes and diagonals.
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Introduction Standing radiographs are the ‘gold standard’ for clinical assessment of adolescent idiopathic scoliosis (AIS), with the Cobb Angle used to measure the severity and progression of the scoliotic curve. Supine imaging modalities can provide valuable 3D information on scoliotic anatomy, however, due to changes in gravitational loading direction, the geometry of the spine alters between the supine and standing position which in turn affects the Cobb Angle measurement. Previous studies have consistently reported a 7-10° [1-3] Cobb Angle increase from supine to standing, however, none have reported the effect of endplate pre-selection and which (if any) curve parameters affect the supine to standing Cobb Angle difference. Methods Female AIS patients with right-sided thoracic major curves were included in the retrospective study. Clinically measured Cobb Angles from existing standing coronal radiographs and fulcrum bending radiographs [4] were compared to existing low-dose supine CT scans taken within 3 months of the reference radiograph. Reformatted coronal CT images were used to measure Cobb Angle variability with and without endplate pre-selection (end-plates selected on the radiographs used on the CT images). Inter and intra-observer measurement variability was assessed. Multi-linear regression was used to investigate whether there was a relationship between supine to standing Cobb Angle change and patient characteristics (SPSS, v.21, IBM, USA). Results Fifty-two patients were included, with mean age of 14.6 (SD 1.8) years; all curves were Lenke Type 1 with mean Cobb Angle on supine CT of 42° (SD 6.4°) and 52° (SD 6.7°) on standing radiographs. The mean fulcrum bending Cobb Angle for the group was 22.6° (SD 7.5°). The 10° increase from supine to standing is consistent with existing literature. Pre-selecting vertebral endplates was found to increase the Cobb Angle difference by a mean 2° (range 0-9°). Multi-linear regression revealed a statistically significant relationship between supine to standing Cobb Angle change with: fulcrum flexibility (p=0.001), age (p=0.027) and standing Cobb Angle (p<0.001). In patients with high fulcrum flexibility scores, the supine to standing Cobb Angle change was as great as 20°.The 95% confidence intervals for intra-observer and inter-observer measurement variability were 3.1° and 3.6°, respectively. Conclusion There is a statistically significant relationship between supine to standing Cobb Angle change and fulcrum flexibility. Therefore, this difference can be considered a measure of spinal flexibility. Pre-selecting vertebral endplates causes only minor changes.