£108.13

CRC Press Green Computing and Predictive Analytics for Healthcare

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Description

Product Description Green Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government Engineering College, Kalyani, West Bengal, India. His research interests include Big Data, Cloud Computing, Distributed Computing and Mobile Communications. Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, WBAN, Wireless Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr. Kousik Dasgupta is an Assistant Professor at the Department of Computer Science and Engineering, Kalyani Government Engineering College, India. His research interests include Computer Vision, AI/ML, Cloud Computing, Big Data and Security. About the Author Dr. Sourav Banerjee achieved Ph.D degree in Computer Science and Engineering from the University of Kalyani in 2017. He completed his B.E in Computer Science and Engineering in the year 2004 and M.Tech in Computer Science and Engineering in 2006. He is currently an Assistant Professor at Department of Computer Science and Engineering of Kalyani Government Engineering College at Kalyani, West Bengal, India. He has authored numerous reputed non-paid SCI journal articles, book chapters and International conferences. He has edited book on Green Cloud Computing. His research interests include Big Data, Blockchain, Cloud Computing, Green Cloud Computing, Cloud Robotics, Distributed Computing and Mobile Communications, IoT. He is a member of IEEE, ACM, IAE and MIR Labs as well. He is a SIG member of MIR Lab, USA. He is an Editorial board member of Wireless Communication Technology. He is the reviewer of IEEE Transactions on Cloud Computing, Wireless Personal Communications, Journal of Ambient Intelligence and Humanized Computing, Journal of Computer Science, Journal of Supercomputing, Future Internet, International Journal of Computers and Applications, Personal and Ubiquitous Computing, Innovat

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
03 December 2020
Listed Since
07 June 2020

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No barcode data available

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