Big Data and Machine Learning
This chapter focusses on the opportunities and challenges of big data and machine learning in relation to oral epidemiology. Big data are characterized as high-volume data that allow for smart data processing and integration of multiple data sources. They
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Marco A. Peres Jose Leopoldo Ferreira Antunes Richard G. Watt Editors
Oral Epidemiology
A Textbook on Oral Health Conditions, Research Topics and Methods
Textbooks in Contemporary Dentistry
This textbook series presents the most recent advances in all fields of dentistry, with the aim of bridging the gap between basic science and clinical practice. It will equip readers with an excellent knowledge of how to provide optimal care reflecting current understanding and utilizing the latest materials and techniques. Each volume is written by internationally respected experts in the field who ensure that information is conveyed in a concise, consistent, and readily intelligible manner with the aid of a wealth of informative illustrations. Textbooks in Contemporary Dentistry will be especially valuable for advanced students, practitioners in the early stages of their career, and university instructors. More information about this series at http://www.springer.com/series/14362
Marco A. Peres • Jose Leopoldo Ferreira Antunes Richard G. Watt Editors
Oral Epidemiology A Textbook on Oral Health Conditions, Research Topics and Methods
Editors
Marco A. Peres National Dental Research Institute, National Dental Centre Singapore Singapore ACP Oral Health, Health Services and Systems Research Programme, Duke-NUS Medical School Singapore, Singapore
Jose Leopoldo Ferreira Antunes School of Public Health University of São Paulo Faculty of Public Health São Paulo, São Paulo, Brazil
Richard G. Watt Dept. of Epidemiology and Public Health University College London London, United Kingdom
Originally published by Livraria Santos Editora Ltda., São Paulo, 2013 ISSN 2524-4612 ISSN 2524-4620 (electronic) Textbooks in Contemporary Dentistry ISBN 978-3-030-50122-8 ISBN 978-3-030-50123-5 (eBook) https://doi.org/10.1007/978-3-030-50123-5 © Springer Nature Switzerland AG 2021 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdiction
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