Applications of Big Data in Healthcare

Theory and Practice
Erscheinungsjahr 2021
ISBN: 978-0-12-820203-6
Verlag: Elsevier Inc

Buch, Englisch, 310 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 537 g

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.

Autoren/Hrsg.

Khanna, Ashish

Gupta, Deepak

Dey, Nilanjan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

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

Über Autor(innen)

Dey, Nilanjan
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.

Khanna, Ashish
Ashish Khanna is Professor in 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. His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning.

Gupta, Deepak
Dr. Deepak Gupta is an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Institute
of 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.