Data Modelling and Analytics for the Internet of Medical Things
eBook - ePub

Data Modelling and Analytics for the Internet of Medical Things

  1. 318 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data Modelling and Analytics for the Internet of Medical Things

About this book

The emergence of the Internet of Medical Things (IoMT) is transforming the management of diseases, improving diseases diagnosis and treatment methods, and reducing healthcare costs and errors. This book covers all the essential aspects of IoMT in one place, providing readers with a comprehensive grasp of IoMT and related technologies.

Data Modelling and Analytics for the Internet of Medical Things integrates the architectural, conceptual, and technological aspects of IoMT, discussing in detail the IoMT, connected smart medical devices, and their applications to improve health outcomes. It explores various methodologies and solutions for medical data analytics in healthcare systems using machine learning and deep learning approaches, as well as exploring how technologies such as blockchain and cloud computing can further enhance data analytics in the e-health domain. Prevalent IoMT case studies and applications are also discussed.

This book is suitable for scientists, design engineers, system integrators, and researchers in the field of IoMT. It will also be of interest to postgraduate students in computer science focusing on healthcare applications and a supplementary reading for IoMT courses.

Frequently asked questions

Yes, you can cancel anytime from the Subscription tab in your account settings on the Perlego website. Your subscription will stay active until the end of your current billing period. Learn how to cancel your subscription.
No, books cannot be downloaded as external files, such as PDFs, for use outside of Perlego. However, you can download books within the Perlego app for offline reading on mobile or tablet. Learn more here.
Perlego offers two plans: Essential and Complete
  • Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
  • Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Both plans are available with monthly, semester, or annual billing cycles.
We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.
Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
Yes! You can use the Perlego app on both iOS or Android devices to read anytime, anywhere — even offline. Perfect for commutes or when you’re on the go.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Data Modelling and Analytics for the Internet of Medical Things by Rajiv Pandey,Pratibha Maurya,Raymond Chiong in PDF and/or ePUB format, as well as other popular books in Technik & Maschinenbau & Elektrotechnik & Telekommunikation. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. About the Editors
  7. Contributors
  8. Preface
  9. Section 1 IoMT Datasets and Storage
  10. Section 2 Machine Learning for Medical Things
  11. Section 3 IoMT: Data Analytics and Use Cases
  12. Index