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Titlebook: Smoking and Lung Inflammation; Basic, Pre-Clinical Thomas J. Rogers,Gerard J. Criner,William D. Cornw Book 2013 Springer Science+Business

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書目名稱Smoking and Lung Inflammation
副標題Basic, Pre-Clinical
編輯Thomas J. Rogers,Gerard J. Criner,William D. Cornw
視頻videohttp://file.papertrans.cn/870/869142/869142.mp4
概述Focus on both basic and clinical research.Unique, with respect to scope of the discussion of the unusual characteristics of the immune response in patients.Will include knowledge being gained from tra
圖書封面Titlebook: Smoking and Lung Inflammation; Basic, Pre-Clinical  Thomas J. Rogers,Gerard J. Criner,William D. Cornw Book 2013 Springer Science+Business
描述.Smoking and Lung Inflammation?is the first book directly related to chronic lung inflammation of its kind in several respects. First, the it focuses on both basic and clinical research on COPD, and the inflammatory mechanisms that function in these diseases. Second,?it is unique with respect to scope of the discussion of the unusual characteristics of the immune response which occurs in these patients. Third,?it includes knowledge being gained from translational research conducted through clinical trials at several Medical Schools in the United States. Not only is this research providing information about novel drugs and therapies, but it is also advancing our understanding of the genetics of these diseases. This work will illuminate the molecular basis for these diseases, and hopefully will permit us to individualize the therapies for these diseases. .
出版日期Book 2013
版次1
doihttps://doi.org/10.1007/978-1-4614-7351-0
isbn_softcover978-1-4939-5571-8
isbn_ebook978-1-4614-7351-0
copyrightSpringer Science+Business Media New York 2013
The information of publication is updating

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Paul A. Kennedy,Laurie E. Kilpatrickresentations for structured tables. Most previous methods roughly flatten the table and send it into a sequence encoder, ignoring the structure information of tables and the semantic interaction between table cells and contexts. In this paper, we propose a dual graph based method to perceive the sem
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Victor Kim M.D.,Kosuke Kato Ph.D.,K. Chul Kim Ph.D.,Erik P. Lillehoj Ph.D. network has been proved to be an effective way to explore the labels dependencies. However, due to the complexity of label semantic relations, the static dependencies obtained by existing methods cannot consider the overall characteristics of an image and accurately locate the target region. Theref
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Changcheng Song Ph.D.,Steven G. Kelsen M.D.tained from a priori unknown network processes is maximized. The uncertainty calls for online learning, which suffers however from the curse of dimensionality. To achieve sample efficiency, we describe the network processes with an adaptive graph dictionary model, which typically leads to sparse spe
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Kartik V. Shenoy,Gerard J. Crinerdomness of physical systems. To account for these factors, existing works estimate the aleatoric uncertainty of object detectors by modeling their localization output as a Gaussian distribution ., and training with loss attenuation. We identify three aspects that are unaddressed in the state of the
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