Deep Learning Techniques for Biomedical and Health Informatics
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life
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Sujata Dash · Biswa Ranjan Acharya · Mamta Mittal · Ajith Abraham · Arpad Kelemen Editors
Deep Learning Techniques for Biomedical and Health Informatics
Studies in Big Data Volume 68
Series Editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
The series “Studies in Big Data” (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence including neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. ** Indexing: The books of this series are submitted to ISI Web of Science, DBLP, Ulrichs, MathSciNet, Current Mathematical Publications, Mathematical Reviews, Zentralblatt Math: MetaPress and Springerlink.
More information about this series at http://www.springer.com/series/11970
Sujata Dash Biswa Ranjan Acharya Mamta Mittal Ajith Abraham Arpad Kelemen •
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Deep Learning Techniques for Biomedical and Health Informatics
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Editors Sujata Dash Department of Computer Science North Orissa University Takatpur, Odisha, India Mamta Mittal Computer Science and Engineering Department G. B. Pant Government Engineering College New Delhi, Delhi, India
Biswa Ranjan Acharya School of Computer Science and Engineering KIIT Deemed to University Bhubaneswar, Odisha, India Ajith Abraham Scientific Network for Innovation and Research Excellence Machine Intelligence Research Labs Auburn, AL, USA
Arpad Kelemen Department of Organizational Systems and Adult Health University of Maryland Baltimore, MD, USA
ISSN 2197-6503 ISSN 2197-6511 (electronic) Studies in Big Data ISBN 978-3-030-33965-4 ISBN 978-3-030-33966-1 (eBook) https://doi.org/10.1007/978-3-030-33966-1 © Springer Nature Switzerland AG 2020 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 sof
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