Machine Learning and the Internet of Medical Things in Healthcare

Krishna Kant Singh, Mohamed Elhoseny, Akansha Singh, Ahmed A. Elngar

• Publisher: Academic Press
• Year: 2021
• ISBN:
  9780128232170
• Topic: Biological Sciences
• Subtopic: Biotechnology
• Index: Biological Sciences

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide.

The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.

• Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning
• Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics
• Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• Chapter 1. Machine learning architecture and framework
• Chapter 2. Machine learning in healthcare: review, opportunities and challenges
• Chapter 3. Machine learning for biomedical signal processing
• Chapter 4. Artificial itelligence in medicine
• Chapter 5. Diagnosing of disease using machine learning
• Chapter 6. A novel approach of telemedicine for managing fetal condition based on machine learning technology from IoT-based wearable medical device
• Chapter 7. IoT-based healthcare delivery services to promote transparency and patient satisfaction in a corporate hospital
• Chapter 8. Examining diabetic subjects on their correlation with TTH and CAD: a statistical approach on exploratory results
• Chapter 9. Cancer prediction and diagnosis hinged on HCML in IOMT environment
• Chapter 10. Parameterization techniques for automatic speech recognition system
• Chapter 11. Impact of big data in healthcare system—a quick look into electronic health record systems
• Index