Emerging Technologies for Healthcare

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Scrivener Publishing100 Cummings Center, Suite 541J Beverly, MA 01915-6106

Publishers at Scrivener

Martin Scrivener ( martin@scrivenerpublishing.com) Phillip Carmical ( pcarmical@scrivenerpublishing.com)

Edited by

Monika Mangla,

Nonita Sharma,

Poonam Mittal,

Vaishali Mehta Wadhwa,

Thirunavukkarasu K.

and

Shahnawaz Khan

This edition first published 2021 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

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Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-79172-0

Cover image: Pixabay.Com

Cover design by Russell Richardson

Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

Printed in the USA

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The use of computing technologies in the healthcare domain has been creating new avenues for facilitating the work of healthcare professionals. Several computing technologies, such as machine learning and virtual reality, have been flourishing and in turn creating new possibilities. Computing algorithms, methodologies and approaches are being used to provide accurate, stable and prompt results. Moreover, deep learning, an advanced learning technique, is striving to enable computing models to mimic the behavior of the human brain; and the Internet-of-Things (IoT), the computer network consisting of “things” or physical objects in addition to sensors, software or methods, is connecting to and exchanging data with other devices. Therefore, the primary focus of this book, Emerging Technologies for Healthcare , is to discuss the use and applications of these IoT and deep learning approaches for providing automated healthcare solutions.

Our motivation behind writing this book was to provide insight gained by analyzing data and information, and in the end provide feasible solutions through various machine learning approaches and apply them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition to this, providing healthcare solutions for post COVID-19 outbreaks through various suitable approaches is also highlighted. Furthermore, a detailed detection mechanism is discussed which is used to come up with solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions.

This book not only covers theoretical approaches and algorithms, but also contains the sequence of steps used to analyze problems with data, processes, reports, and optimization techniques. It will serve as a single source for solving various problems via machine learning algorithms. In brief, this book starts with an IoT-based solution for the automated healthcare sector and extends to providing solutions with advanced deep learning techniques.