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Green Computing and Predictive Analytics for Healthcare [Kietas viršelis]

Edited by (Kalyani Govt. Engg. College, WB, India.), Edited by (BITS Mesra, Jharkhand, India), Edited by (Kalyani Govt. Engg. College, WB, India.)
  • Formatas: Hardback, 190 pages, aukštis x plotis: 254x178 mm, weight: 521 g, 18 Tables, black and white; 39 Illustrations, black and white
  • Išleidimo metai: 11-Dec-2020
  • Leidėjas: Chapman & Hall/CRC
  • ISBN-10: 0367322005
  • ISBN-13: 9780367322007
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 190 pages, aukštis x plotis: 254x178 mm, weight: 521 g, 18 Tables, black and white; 39 Illustrations, black and white
  • Išleidimo metai: 11-Dec-2020
  • Leidėjas: Chapman & Hall/CRC
  • ISBN-10: 0367322005
  • ISBN-13: 9780367322007
Kitos knygos pagal šią temą:
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 masters 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.
Preface vii
About the Editors xi
List of Contributors
xiii
1 Healthcare Data Monitoring under Internet of Things
1(18)
Chinmay Chakraborty
Sanjukta Bhattacharya
2 A Framework for Emergency Remote Care and Monitoring Using Internet of Things
19(22)
Varsha Poddar
3 Big Data Analytics and K-Means Clustering
41(24)
R. Sandhiya
4 Machine Learning-Based Rapid Prediction of Sudden Cardiac Death (SCD) Using Precise Statistical Features of Heart Rate Variability for Single Lead ECG Signal
65(16)
Prakash Banerjee
5 Computer Vision for Brain Tissue Segmentation
81(14)
M. Sucharitha
Chinmay Chakraborty
S. Srinivasa Rao
V. Siva Kumar Reddy
6 A Study on Energy-Efficient and Green IoT for Healthcare Applications
95(20)
B. Arthi
M. Aruna
S. Ananda Kumar
7 Cyber Security in Terms of IoT System and Blockchain Technologies in E-Healthcare Systems
115(30)
Sudipta Paul
Subhankar Mishra
8 Domestic Medical Tourism for National Healthcare Systems
145(14)
Sukanya Roy
9 Study on Edge Computing Using Machine Learning Approaches in IoT Framework
159(24)
Pramit Brata Chanda
Surojit Das
Sourav Banerjee
Chinmay Chakraborty
Index 183
Sourav Banerjee, Chinmay Chakraborty, Kousik Dasgupta