Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians.
The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data.
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Table of Contents
1.Big Data classification: techniques and tools 2.Big Data Analytics for healthcare: theory and applications 3.Application of tools and techniques of Big data analytics for healthcare system 4.Healthcare and medical Big Data analytics 5.Big Data analytics in medical imaging 6.Big Data analytics and artificial intelligence in mental healthcare 7.Big Data based breast cancer prediction using kernel support vector machine with the Gray Wolf Optimization algorithm 8.Big Data based medical data classification using oppositional Gray Wolf Optimization with kernel ridge regression 9.An analytical hierarchical process evaluation on parameters Apps-based Data Analytics for healthcare services 10.Firefly-Binary Cuckoo Search Technique based heart disease prediction in Big Data Analytics 11.Hybrid technique for heart diseases diagnosis based on convolution neural network and long short-term memory
Authors
Ashish Khanna Sr. Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology (MAIT), New Delhi, India. Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research and development. He received his PhD from the National Institute of Technology, Kurukshetra, India, and completed a post-doc degree at the National Institute of Telecommunications (Inatel), Brazil. He has published around 40 SCI-indexed papers in 'IEEE Transactions', and in other reputed journals by Springer, Elsevier, and Wiley, with a cumulative impact factor of above 100. He has published around 90 research articles in top SCI/Scopus journals, conferences, and book chapters. He is co-author or editor of numerous books, including 'Advanced Computational Techniques for Virtual Reality in Healthcare' (Springer), 'Intelligent Data Analysis: From Data Gathering to Data Comprehension' (Wiley), and 'Hybrid Computational Intelligence: Challenges and Applications' (Elsevier). His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning. He is one of the founders of Bhavya Publications and the Universal Innovator Lab, which is actively involved in research, innovation, conferences, start-up funding events, and workshops. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India, and is also a Visiting Professor at the University of Valladolid, Spain. Deepak Gupta Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, India. Dr. Deepak Gupta is an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Instituteof Technology, Guru Gobind Singh Indraprastha University, India. He obtained his PhD from Dr. APJ Abdul Kalam Technical
University. He is a post doc research fellow in the Internet of Things research lab at Inatel, Brazil. He has been guest editor for 10
special journal issues, including ASoC (Elsevier), NCAA (Springer), Sensors (MPDI) and CAEE (Elsevier). He is Editor-in-Chief
of OA Journal - Computers and Associate Editor of Journal of Computational and Theoretical Nanoscience. Nilanjan Dey Associate Professor, Department of Computer Science and Engineering, Techno International New Town, Kolkata, India.
Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He also holds a position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence , IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (SpringerNature), Data-Intensive Research(SpringerNature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He was an associate editor of IET Image Processing and editorial board member of Complex & Intelligent Systems, Springer Nature. He is an editorial board member of Applied Soft Computing, Elsevier. He is having 35 authored books and over 300 publications in the area of medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Fellow of IETE and Senior member of IEEE.
