Machine Learning and the Internet of Medical Things in Healthcare
eBook - ePub

Machine Learning and the Internet of Medical Things in Healthcare

  1. 290 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Machine Learning and the Internet of Medical Things in Healthcare

About this book

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

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Yes, you can access Machine Learning and the Internet of Medical Things in Healthcare by Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Biotechnology. We have over one million books available in our catalogue for you to explore.

Table of contents

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