Machine Learning in Medicine - Cookbook
The amount of data in medical databases doubles every 20 months, and physicians are at a loss to analyze them. Also, traditional methods of data analysis have difficulty to identify outliers and patterns in big data and data with multiple exposure / outco
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Ton J. Cleophas Aeilko H. Zwinderman
Machine Learning in Medicine Cookbook
SpringerBriefs in Statistics
For further volumes: http://www.springer.com/series/8921
Ton J. Cleophas Aeilko H. Zwinderman •
Machine Learning in Medicine - Cookbook
123
Aeilko H. Zwinderman Department Biostatistics and Epidemiology Academic Medical Center Amsterdam The Netherlands
Ton J. Cleophas Department Medicine Albert Schweitzer Hospital Sliedrecht The Netherlands
Additional material to this book can be downloaded from http://www.extras.springer.com.
ISSN 2191-544X ISBN 978-3-319-04180-3 DOI 10.1007/978-3-319-04181-0
ISSN 2191-5458 (electronic) ISBN 978-3-319-04181-0 (eBook)
Springer Cham Heidelberg New York Dordrecht London Library of Congress Control Number: 2013957369 The Author(s) 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The amount of data stored in the world’s databases doubles every 20 months, as estimated by Usama Fayyad, one of the founders of machine learning and coauthor of the book ‘‘Advances in knowledge discovery and data mining’’ (ed. by the American Association for Artificial Intelligence, Menlo Park, CA, USA, 1996), and clinicians, familiar with traditional statistical methods, are at a loss to analyze them. Traditional methods have
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