Internet of Things enabled Machine Learning for Biomedical Application

Cover
	Half Title
Title Page
Copyright Page
Contents
List of contributors
Editors’ biographies
1. ML and IoT coupled biomedical applications in healthcare: Smart growth and upcoming challenges
2. Recent advances in ubiquitous sustainable healthcare systems
3. IoT-enabled healthcare system using machine learning
4. An efficient architecture for classification of super-resolution enhanced human chromosome images
5. Applications of machine learning to the impact of IoT in biomedical applications
6. Ovarian cancer detection using IoT-based intelligent assistant and blockchain technology
7. Blood oxygen level and pulse rate measurement using hemodialysis using IoT and computational intelligence
8. Dental shade matching using machine learning models
9. Brain tumor detection for recognizing critical brain damage in patients using computer vision
10. Smart therapist: The mental health detector
11. Medical image analysis based on deep learning approach and Internet of Medical Things (IoMT) for early diagnosis of retinal disease
12. Intelligent e-learning platform consolidating Web of Things and ChatGPT
13. Issues and challenges in security and privacy with e-Healthcare: A thorough literature analysis
14. Harnessing the power of distributed cloud and edge computing for advanced healthcare systems
15. Securing cloud-based IoT: Exploring the significance of lightweight cryptography for enhanced security
16. Security and privacy in the Internet of Medical Things (IoMT)-based healthcare: Ensuring trust and safety
17. A comprehensive study of the problem and challenges associated with machine learning-enabled IoT in biomedical applications
18. A machine learning-enabled Internet of Things model for cloud-based biomedical applications
19. Machine learning-enabled IoT for biomedical applications: Problem and challenges
20. IoT-driven machine learning mechanisms for healthcare applications
Index