Principles of Supervised Learning

The medical literature has many examples of predictive models based on multiple regression and logistic regression, collectively referred to as supervised machine learning. Both methods actually have fairly stringent “assumptions,” which are often not met

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Volume 1: Quantitative Approaches in Health Systems Engineering Peter J. Fabri

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Measurement and Analysis in Transforming Healthcare Delivery

Peter J. Fabri

Measurement and Analysis in Transforming Healthcare Delivery Volume 1: Quantitative Approaches in Health Systems Engineering

Peter J. Fabri Colleges of Medicine and Engineering University of South Florida Tampa, FL, USA

ISBN 978-3-319-40810-1 ISBN 978-3-319-40812-5 DOI 10.1007/978-3-319-40812-5

(eBook)

Library of Congress Control Number: 2016943088 © Springer International Publishing Switzerland 2016 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. 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland

To my loving wife, Sharon, who put up with me through the struggles of returning to graduate school, who actually understood why a successful academic surgeon would start all over in order to develop a new approach to “fixing healthcare,” and who encouraged me to write this book. To my children, Christopher and Andrea, who still think I’m crazy. To Tony Dorfmueller, who introduced me to Total Quality Management and Continuous Quality Improvement long before these concepts were recognized in healthcare. To Thomas Graf MD who provided expert feedback. To Louis MartinVega PhD and Jose Zayas-Castro PhD who believed in me and allowed me to pursue a PhD in Industrial Engineering 36 years after I completed college and without any prior education in engineering [3]. And to my students, both in medicine and in engineering, who helped me formulate new ways to explain difficult analytical and quantitative concepts.

Preface

In general, one might conclude that relatively too much scientific effort has been expended hitherto in the production of new devices and too little in the proper use of what we have got. Patrick Maynard Stuart Blackett, Baron Blackett OM CH PRS [1]

In the opening salvos of the Second World War, Britai

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