Sunil Kumar Dhal (editor) - Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics: Concepts, Methodologies, Tools and Applications (Advances in Intelligent and Scientific Computing)

Scrivener Publishing

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Bioprocessing in Food Science

Series Editor: Anil Panghal, PhD

Publishers at Scrivener

Martin Scrivener ()

Phillip Carmical ()

Edited by

Sunil Kumar Dhal

ASubhendu Kumar Pani

Srinivas Prasad

and

Sudhir Kumar Mohapatra

This edition first published 2022 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 2022 Scrivener Publishing LLC

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Library of Congress Cataloging-in-Publication Data

ISBN 9781119791737

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 novel applications of Big Data Analytics and machine intelligence in biomedical and healthcare sector can be regarded as an emerging field in computer science, medicine, biology application, natural environmental engineering, and pattern recognition. The use of various Data Analytics and intelligence techniques are nowadays successfully implemented in many healthcare sectors. Biomedical and Health Informatics is a new era that brings tremendous opportunities and challenges due to easily available plenty of biomedical data. Machine learning presenting tremendous improvement in accuracy, robustness, and cross-language generalizability over conventional approaches. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant biomedical, and healthcare data. Earlier, it was common requirements to have a domain expert to develop a model for biomedical or healthcare; but now the patterns are learned automatically for prediction. Due to the rapid advances in intelligent algorithms have established the growing significance in healthcare data analytics. The IoT focuses to the common idea of things that is recognizable, readable, locatable, controllable, and addressable via the Internet. Intelligent Learning aims to provide computational methods for accumulating, updating and changing knowledge in the intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In Future Big data analytics has the impending capability to change the way we work and live. With the influence and the development of the Big Data, IoT concept, the need for AI (Artificial Intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent system generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Intelligent systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics etc.

This book covers the latest advances and developments in health informatics, data mining, machine learning and artificial intelligence, fields which to a great extent will play a vital role in improving human life. All the researchers and practitioners will be highly benefited those are working in field of biomedical, health informatics, Big Data Analytics, IoT and Machine Learning. This book would be a good collection of state-of-the-art approaches for Big Data and Intelligent based biomedical and health related applications. It will be very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book would be very useful because there is no book in the market which provides a good collection of state-of-the-art methods of Big Data, machine learning and IoT in Biomedical and Health Informatics. Various models for biomedical and health informatics is recently emerged and very unmatured field of research in biomedical and healthcare. This book would be very useful because there is no book in the market which provides a good collection of state-of-the-art methods of for Big data analytics based models for healthcare.

The 12 chapters of this book present scientific concepts, frameworks and ideas on biomedical data analytics from the different biomedical domains. The Editorial Advisory Board and expert reviewers have ensured the high caliber of the chapters through careful refereeing of the submitted papers. For the purpose of coherence, we have organized the chapters with respect to similarity of topics addressed, ranging from issues pertaining to the internet of things for biomedical engineering and health informatics, computational intelligence for medical data processing and Internet of medical things.