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Full Description
This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The book provides in-depth discussion about the security issues and protocols for pervasive healthcare. This book explores concepts and techniques behind the successive pervasive healthcare systems by providing in-depth knowledge about patient empowerment, remote patient monitoring, network establishment and protocols for effective pervasive healthcare. The book also provides case studies in the field. It is an ideal resource for researchers, students and healthcare organizations to get insight about the state of the art in pervasive healthcare systems.
Provides current research, developments, and applicationsin pervasive healthcare;
Includes technologies such as machine learning, cryptography, fog computing, and big data in the advancement of e-healthcare;
Pertinent for researchers, students, practitioners and healthcare decision makers.
Contents
Introduction.- Hybrid Machine Learning Techniques for Reliability and Security of Healthcare IoT Data.- Cryptographic Operations and Approaches for Privacy of IoT Data in healthcare.- Standards and Approaches for use of Blockchain Technology in Pervasive Healthcare.- Prediction of REM sleep behaviour disorder using EEG signal applied EMG 1 EMG 2 channel.- Healthcare Assisted by Fog Computing for Secure Data Transmission in Healthcare IoTs.- Experimental approaches for prediction of breast cancer diseases using clustering concepts.- Incident reporting system for Pervasive Healthcare.- Blockchain Application for Healthcare record management.- Applying Machine Learning Approach for Disease prediction.- Mobile system for remote patient monitoring.- Securing Pervasive Healthcare system.- Remote Patient Monitoring: Benefits, Applications and Issues.- Self-reporting in Pervasive Healthcare.- Role of Big Data Analytics in Pervasive Healthcare.- ML Techniques for remote patient activity monitoring.- Trust Management in Pervasive Healthcare.- Disease Detection using Android App.- Application of computer assisted machine learning based techniques in detecting neurological disorders.- Conclusion.
