Healthcare Data Analytics and Management Advances in ubiquitous sensing applications for healthcare Series
Coordonnateurs : Dey Nilanjan, Ashour Amira S., James Fong Simon, Bhatt Chintan
Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data.
1. Internet of Things, Smart Sensors,and Pervasive Systems: Enabling the Connected and Pervasive Health Care 2. Migration of Healthcare Relational Database to NoSQL Cloud Database for Healthcare Analytics and Management 3. Developing a Decision Support System for Big Data Analysis and Cost Allocation in National Health Care 4. Securing Large Datasets Involving Fast performing Key Bunch Matrix Block Cipher 5. Comparative Analysis of Semantic Framework in Healthcare 6. Smart Ambulance System Using Concept of Big Data and Internet of Things 7. Mathematical methods of ECG data analysis 8. Smart Information Technology for Universal Health Care 9. Handling Uncertainty in IoT Design: An Approach of Statistical Machine Learning with Distributed Second order Optimization 10. A reversible and secure Electronic Patient Record (EPR) embedding technique using histogram bin shifting and RC6 encryption 11. Secure and Reversible Data Hiding Scheme for Healthcare System using Magic Rectangle and a new Interpolation Technique
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.
Amira S. Ashour is an Assistant Professor and Head of Electronics and Electrical Communications Engineering Department, Faculty of Engineering, Tanta University, Egypt. She is a member in the Research and Development Unit, Faculty of Engineering, Tanta University, Egypt. She received the B.Eng. degree in Electrical Engineering from Faculty of Engineering, Tanta University, Egypt in 1997, M.Sc. in Image Processing in 2001 and Ph.D. in Smart Antenna in 2005 from Faculty of Engineering, Tanta University, Egypt. Ashour has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the vice chair of CS department, CIT college, Taif University, KSA for 5 years. Her research interests a
- Covers data analysis, management and security concepts and tools in the healthcare domain
- Highlights electronic medical health records and patient information records
- Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining
- Includes multidisciplinary contributions in relation to healthcare applications and challenges
Date de parution : 11-2018
Ouvrage de 340 p.
19x23.3 cm
