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Titlebook: Evidence Based Pathology and Laboratory Medicine; Alberto M. Marchevsky,Mark Wick Book 2011 Springer Science+Business Media, LLC 2011 Baye

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書目名稱Evidence Based Pathology and Laboratory Medicine
編輯Alberto M. Marchevsky,Mark Wick
視頻videohttp://file.papertrans.cn/318/317507/317507.mp4
概述Focuses on practical patient related issues.Develops diagnostic models.Use of meta-analysis to investigate unusual diseases.Includes supplementary material:
圖書封面Titlebook: Evidence Based Pathology and Laboratory Medicine;  Alberto M. Marchevsky,Mark Wick Book 2011 Springer Science+Business Media, LLC 2011 Baye
描述.Focusing on practical, patient related issues, this volume provides the basic concepts of Evidence Based Medicine (EBM) as they relate to Pathology and Laboratory Medicine and presents various practical applications. It includes EBM concepts for use in the identification of cost-effective panels of immunostains and other laboratory tests and for improvement of diagnostic accuracy based on the identification of selected diagnostic features for particular differential diagnosis. EBM concepts are also put forth for use in Meta-analysis to integrate the results of conflicting literature reports and use of novel analytical tools such as Bayesian belief networks, neural networks, multivariate statistics and decision tree analysis for the development of new diagnostic and prognostic models for the evaluation of patients. This volume will be of great value to pathologists who will benefit from the concepts being promoted by EBM, such as levels of evidence, use of Bayesian statistics to develop diagnostic and other rules and stronger reliance on "hard data" to support therapeutic and diagnostic modalities..
出版日期Book 2011
關(guān)鍵詞Bayesian statistics; Immunostains; Laboratory tests; Meta-analysis; Neural networks
版次1
doihttps://doi.org/10.1007/978-1-4419-1030-1
isbn_softcover978-1-4939-5110-9
isbn_ebook978-1-4419-1030-1
copyrightSpringer Science+Business Media, LLC 2011
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https://doi.org/10.1007/978-1-4419-1030-1Bayesian statistics; Immunostains; Laboratory tests; Meta-analysis; Neural networks
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ill benefit from the concepts being promoted by EBM, such as levels of evidence, use of Bayesian statistics to develop diagnostic and other rules and stronger reliance on "hard data" to support therapeutic and diagnostic modalities..978-1-4939-5110-9978-1-4419-1030-1
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Introduction to Evidence-Based Pathology and Laboratory Medicine
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Prognostication and Prediction in Anatomic Pathology: Carcinoma of the Breast as an Illustrative Mod
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