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Titlebook: Clinical Prediction Models; A Practical Approach Ewout W. Steyerberg Book 20091st edition Springer-Verlag New York 2009 An?sthesie-Informat

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發(fā)表于 2025-3-21 18:21:23 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Clinical Prediction Models
副標(biāo)題A Practical Approach
編輯Ewout W. Steyerberg
視頻videohttp://file.papertrans.cn/229/228183/228183.mp4
概述A sensible strategy to all three aspects (development, validation, updating) is relevant to provide up-to-date prognostic models that can reliably support medical practice.Includes supplementary mater
叢書名稱Statistics for Biology and Health
圖書封面Titlebook: Clinical Prediction Models; A Practical Approach Ewout W. Steyerberg Book 20091st edition Springer-Verlag New York 2009 An?sthesie-Informat
描述Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book? My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is
出版日期Book 20091st edition
關(guān)鍵詞An?sthesie-Informations-Management-System; Data-analysis; Evidence-Based Medicine; Prediction; Radiologi
版次1
doihttps://doi.org/10.1007/978-0-387-77244-8
isbn_ebook978-0-387-77244-8Series ISSN 1431-8776 Series E-ISSN 2197-5671
issn_series 1431-8776
copyrightSpringer-Verlag New York 2009
The information of publication is updating

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發(fā)表于 2025-3-21 23:37:31 | 只看該作者
Statistical Models for Prediction,on the most relevant aspects of these models in a prediction context. All models are illustrated with case studies. In Chap. 6, we will discuss aspects of choosing between alternative statistical models.
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Assumptions in regression models:Additivity and linearity,egies to extend a prediction model with interactions and non-linear terms, since better fulfillment of assumptions in a particular sample does not necessarily imply better predictive performance for future subjects. We consider several case studies for illustration of various strategies to deal with additivity and linearity.
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發(fā)表于 2025-3-22 11:21:15 | 只看該作者
Book 20091st editionin the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-ba
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Evaluation of performance,lly relevant for prediction of binary outcomes in individual patients. We will illustrate the use of performance measures in the testicular cancer case study, with model development in 544 patients, internal validation with bootstrapping, and external validation with 273 patients from another centre.
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Restrictions on candidate predictors,predictors, combining similar variables, and averaging the effects of similar variables. We provide a detailed description of a case study of modelling similar effects of aspects of family history for robust prediction of the presence of a genetic mutation.
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