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This book reviews that narrate the development of current technologies under the theme of the emerging concept of healthcare, specifically in terms of what makes healthcare more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is machine learning, deep learning, big data, and Internet of Things (IoT)―the scientific field that gives machines the ability to learn without being strictly programmed. It has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data-intensive processes in healthcare operational environments.
This book offers comprehensive coverage of the most essential topics, including:
Introduction to e-monitoring for healthcareCase studies based on big data and healthcareIntelligent learning analytics in healthcare sectors using machine learning and IoTIdentifying diseases and diagnosis using machine learning and IoTDeep learning architecture and framework for healthcare using IoTKnowledge discovery from big data of healthcare-related processingBig data and IoT in healthcareRole of IoT in sustainable healthcareA heterogeneous IoT-based application for remote monitoring of physiological and environmental parameters
Preface
Acknowledgements
Editors
List of Contributors
Introduction to E-Monitoring for Healthcare
Case Study-Based Big Data and IoT in Healthcare
Intelligent Learning Analytics in the Healthcare Sector Using Machine Learning and IoT
Influence of AI and Machine Learning to Empower the Healthcare Sector
Real-Time IoT-Based Online Analysis to Improve Performance of PV Solar System for Medical Emergencies
Major Depressive Disorder Detection and Monitoring Using Smart Wearable Devices with Multi-Feature Sensing
IoT in the Healthcare Sector
The Role of IoT in Sustainable Healthcare
EMG-Based Robot Control Human Interfaces for Hospitals
Performance Analysis of Adaptive Cruise Control Using Arduino for Healthcare
Index