3,008 research outputs found

    Efficacy of interspinous device versus surgical decompression in the treatment of lumbar spinal stenosis: a modified network analysis.

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    Study designSystematic review using a modified network analysis.ObjectivesTo compare the effectiveness and morbidity of interspinous-device placement versus surgical decompression for the treatment of lumbar spinal stenosis.SummaryTraditionally, the most effective treatment for degenerative lumbar spinal stenosis is through surgical decompression. Recently, interspinous devices have been used in lieu of standard laminectomy.MethodsA review of the English-language literature was undertaken for articles published between 1970 and March 2010. Electronic databases and reference lists of key articles were searched to identify studies comparing surgical decompression with interspinous-device placement for the treatment of lumbar spinal stenosis. First, studies making the direct comparison (cohort or randomized trials) were searched. Second, randomized controlled trials (RCTs) comparing each treatment to conservative management were searched to allow for an indirect comparison through a modified network analysis approach. Comparison studies involving simultaneous decompression with placement of an interspinous device were not included. Studies that did not have a comparison group were not included since a treatment effect could not be calculated. Two independent reviewers assessed the strength of evidence using the GRADE criteria assessing quality, quantity, and consistency of results. The strengths of evidence for indirect comparisons were downgraded. Disagreements were resolved by consensus.ResultsWe identified five studies meeting our inclusion criteria. No RCTs or cohort studies were identified that made the direct comparison of interspinous-device placement with surgical decompression. For the indirect comparison, three RCTs compared surgical decompression to conservative management and two RCTs compared interspinous-device placement to conservative management. There was low evidence supporting greater treatment effects for interspinous-device placement compared to decompression for disability and pain outcomes at 12 months. There was low evidence demonstrating little to no difference in treatment effects between the groups for walking distance and complication rates.ConclusionThe indirect treatment effect for disability and pain favors the interspinous device compared to decompression. The low evidence suggests that any further research is very likely to have an important impact on the confidence in the estimate of effect and is likely to change the estimate. No significant treatment effect differences were observed for postoperative walking distance improvement or complication rates; however, findings should be considered with caution because of indirect comparisons and short follow-up periods

    Efficient Estimation of Word Representations in Vector Space

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    We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Furthermore, we show that these vectors provide state-of-the-art performance on our test set for measuring syntactic and semantic word similarities

    Towards Robust Design and Training of Deep Neural Networks

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    Currently neural networks run as software, which typically requires expensive GPU resources. As the adoption of deep learning continues for a more diverse range of applications, direct hardware implemented neural networks (HNN) will provide deep learning solutions at far lower hardware requirements. However, Gaussian noise along hardware connections degrades model accuracy, an issue this research seeks to resolve using a novel analog error correcting code (ECC). To aid in developing noise tolerant deep neural networks (DNN), this research also investigates the impact of loss functions on training. This involves alternating multiple loss functions throughout training, aiming to prevent local optimals. The effects on training time and final accuracy are then analyzed. This research investigates analog ECCs and loss function variation to allow for future noise tolerant HNN networks. ECC results demonstrate three to five decibel improvements to model accuracy when correcting Gaussian noise. Loss variation results demonstrate a correlation between loss function similarity and training performance. Other correlations are also presented and addressed

    An experimental study of the effects of army recruitment television advertising on high school seniors

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    In order for Army recruiters in the Appalachian region to effectively reach their target audience through television advertising, they must know which segment within the overall stated target audience of high school seniors between the ages of 17 to 21 are most likely to be influenced by Army recruitment advertising. Recruiters must also determine the type of programming preferred by the primary target segment to enable recruiting messages to be placed in programming where it is likely to have the most impact and achieve maximum frequency of exposure among the most receptive audience

    Doctor of Philosophy

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    dissertationExchanging patient specific information across heterogeneous information systems is a critical but increasingly complex and expensive challenge. Lacking a universal unique identifier for healthcare, patient records must be linked using combinations of identity attributes such as name, date of birth, and sex. A state's birth certificate registry contains demographic information that is potentially very valuable for identity resolution, but its use for that purpose presents numerous problems. The objectives of this research were to: (1) assess the frequency, extent, reasons, and types of changes on birth certificates; (2) develop and evaluate an ontology describing information used in identity resolution; and (3) use a logical framework to model identity transactions and assess the impact of policy decisions in a cross jurisdictional master person index. To understand birth certificate changes, we obtained de identifified datasets from the Utah birth certifificate registry, including history and reasons for changes from 2000 to 2012. We conducted cohort analyses, examining the number, reason, and extent of changes over time, and cross sectional analyses to assess patterns of changes. We evaluated an ontological approach to overcome heterogeneity between systems exchanging identity information and demonstrated the use of two existing ontologies, the Simple Event Model (SEM) and the Clinical Element Model (CEM), to capture an individual's identity history. We used Discrete Event Calculus to model identity events iv across domains and over time. Models were used to develop contextual rules for releasing minimal information from birth certificate registries for sensitive cases such as adoptions. Our findings demonstrate that the mutability of birth certificates makes them a valuable resource for identity resolution, provided that changes can be captured and modeled in a usable form. An ontology can effectively model identity attributes and the events that cause them to change over time, as well as to overcome syntactic and semantic heterogeneity. Finally, we show that dynamic, contextual rules can be used to govern the flow of identity information between systems, allowing entities to link records in the most difficult cases, avoid costly human review, and avoid the threats to privacy that come from such review

    Introduction

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