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Internet of Things and Big Data Technologies for Next Generation Healthcare

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Cover of 'Internet of Things and Big Data Technologies for Next Generation Healthcare'

Table of Contents

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    Book Overview
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    Chapter 1 Internet of Things Driven Connected Healthcare
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    Chapter 2 Internet of Things in HealthCare
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    Chapter 3 Energy Efficient Network Design for IoT Healthcare Applications
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    Chapter 4 Exploring Formal Strategy Framework for the Security in IoT towards e-Health Context using Computational Intelligence
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    Chapter 5 Vitality of Robotics in Healthcare Industry: An Internet of Things (IoT) Perspective
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    Chapter 6 Internet of Things Meets Mobile Health Systems in Smart Spaces: An Overview
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    Chapter 7 Big Data Knowledge System in Healthcare
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    Chapter 8 Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms
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    Chapter 9 Co-creation and Participatory Design of Big Data Infrastructures on the Field of Human Health Related Climate Services
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    Chapter 10 Information and Communication Emerging Technology: Making Sense of Healthcare Innovation
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    Chapter 11 Health Informatics as a Service (HIaaS) for Developing Countries
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    Chapter 12 Analysis of Power Aware Protocols and Standards for Critical E-Health Applications
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    Chapter 13 Social Network Analysis in Healthcare
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    Chapter 14 A Decision Support System in Brain Tumor Detection and Localization in Nominated Areas in MR Images
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    Chapter 15 Detecting Unusual Human Activities Using GPU-Enabled Neural Network and Kinect Sensors
Attention for Chapter 7: Big Data Knowledge System in Healthcare
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Chapter title
Big Data Knowledge System in Healthcare
Chapter number 7
Book title
Internet of Things and Big Data Technologies for Next Generation Healthcare
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-49736-5_7
Book ISBNs
978-3-31-949735-8, 978-3-31-949736-5

Gunasekaran Manogaran, Chandu Thota, Daphne Lopez, V. Vijayakumar, Kaja M. Abbas, Revathi Sundarsekar


Chintan Bhatt, Nilanjan Dey, Amira S. Ashour

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 23%
Student > Master 13 17%
Researcher 10 13%
Student > Doctoral Student 7 9%
Student > Bachelor 5 7%
Other 11 15%
Unknown 12 16%
Readers by discipline Count As %
Computer Science 30 40%
Engineering 8 11%
Medicine and Dentistry 4 5%
Agricultural and Biological Sciences 3 4%
Business, Management and Accounting 3 4%
Other 9 12%
Unknown 18 24%