Big Data Analytics for Intelligent Healthcare Management

by Nilanjan Dey PhD (Editor), Himansu Das (Editor), Bighnaraj Naik (Editor), H S Behera (Editor)

Overview

Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. - Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more - Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. - Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Product Details

ISBN-13:	9780128181478
Publisher:	Elsevier Science & Technology Books
Publication date:	04/15/2019
Series:	Advances in ubiquitous sensing applications for healthcare
Sold by:	Barnes & Noble
Format:	eBook
Pages:	312
File size:	43 MB
Note:	This product may take a few minutes to download.

About the Author

Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc. He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.
Himansu Das is working as an as Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He has received his B. Tech and M. Tech degree from Biju Pattnaik University of Technology (BPUT), Odisha, India. He has published several research papers in various international journals and conferences. He has also edited several books of international repute. He is associated with different international bodies as Editorial/Reviewer board member of various journals and conferences. He is a proficient in the field of Computer Science Engineering and served as an organizing chair, publicity chair and act as member of program committees of many national and international conferences. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc., His research interest includes Grid Computing, Cloud Computing, and Machine Learning. He has also 10 years of teaching and research experience in different engineering colleges.
Bighnaraj Naik is an Assistant Professor in the Department of Computer Application, Veer Surendra Sai University of Technology (formerly UCE Burla), Odisha, India. He has published more than 100 research articles in various peer reviewed international journals, conferences, and book chapters. He has edited 10 books for publishers including Elsevier, Springer, and IGI Global. At present, he has more than 10 years of teaching experience in the field of computer science and information technology. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and his areas of interest include data science, data mining, machine learning, deep learning, computational intelligence (CI), and CI’s applications in science and engineering. He has served as Guest Editor of various special issues of journals such as Information Fusion (Elsevier), Neural Computing and Applications (Springer), Evolutionary Intelligence (Springer), International Journal of Computational Intelligence Studies (Inderscience), and International Journal of Swarm Intelligence (Inderscience). He is an active reviewer of various journals from publishers including IEEE Transactions, Elsevier, Springer, and Inderscience. Currently, he is undertaking a major research project as Principal Investigator, which is funded by the Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India.
Dr. Himansu Sekhar Behera is currently working as an Associate Professor and Head of the Department of Information Technology, Veer Surendra Sai University of Technology (VSSUT), India. He received his Doctor of Philosophy in Engineering (Ph.D.) from Biju Pattnaik University of Technology (BPUT), India. His research and development experience includes over 19 years in academia spanning different technical Institutes in India. His research interests include Data Mining, Soft Computing, Evolutionary Computation, Machine Intelligence and Distributed Systems. He has authored or co-authored over 100 research papers various international conferences and journals, as well as contributing several book chapters. He has edited 11 books and serves as an associate editor / member of the editorial board of various international journals and also guest edited 8 special issues on various topics of Inderscience and IGI Global Journals.

Table of Contents

1. Bio-Inspired Algorithms for Big Data Analytics: A Survey, Taxonomy, and Open Challenges2. Big Data Analytics Challenges and Solutions3. Big Data Analytics in Healthcare: A Critical Analysis4. Transfer Learning and Supervised Classifier Based Prediction Model for Breast Cancer5. Chronic TTH Analysis by EMG and GSR Biofeedback on Various Modes and Various Medical Symptoms Using IoT6. Multilevel Classification Framework of fMRI Data: A Big Data Approach7. Smart Healthcare: An Approach for Ubiquitous Healthcare Management Using IOT8. Blockchain in Healthcare: Challenges and Solutions9. Intelligence-Based Health Recommendation System Using Big Data Analytics10. Computational Biology Approach in Management of Big Data of Healthcare Sector11. Kidney-Inspired Algorithm and Fuzzy Clustering for Biomedical Data Analysis

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From the Publisher

A comprehensive guide to the application of Big Data analytics for biomedical engineering and clinical and healthcare research and management