Internet of Things and Machine Learning for Type I and Type II Diabetes
eBook - PDF
Available until 21 Sep |Learn more

Internet of Things and Machine Learning for Type I and Type II Diabetes

Use cases

  1. 500 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF
Available until 21 Sep |Learn more

Internet of Things and Machine Learning for Type I and Type II Diabetes

Use cases

Book details
Table of contents
Citations

About This Book

I nternet of Things and Machine Learning for?Type I and Type II Diabetes: Use Cases provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research community, crossing various sectors for broad coverage of the concepts, themes, and instrumentalities of this important and evolving area. Coverage includes IoT, AI, Deep Learning, Machine Learning and Big Data Analytics for diabetes and health informatics.

  • Integrates many Machine learning techniques in biomedical domain to detect various types of diabetes to utilizing large volumes of available diabetes-related data for extracting knowledge
  • It integrates data mining and IoT techniques to monitor diabetes patients using their medical records (HER) and administrative data
  • Includes clinical applications to highlight contemporary use of these machine learning algorithms and artificial intelligence-driven models beyond research settings

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Yes, you can access Internet of Things and Machine Learning for Type I and Type II Diabetes by Sujata Dash, Subhendu Kumar Pani, Willy Susilo, Cheung Man Yung Bernard, Gary Tse, Sujata Dash,Subhendu Kumar Pani,Willy Susilo,Cheung Man Yung Bernard,Gary Tse in PDF and/or ePUB format, as well as other popular books in Medicine & Neurology. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Elsevier
Year
2024
ISBN
9780323956932
Topic
Medicine
Subtopic
Neurology

Table of contents

  1. Front Cover
  2. INTERNET OF THINGS AND MACHINE LEARNING FOR TYPE I AND TYPE II DIABETES
  3. INTERNET OF THINGS AND MACHINE LEARNING FOR TYPE I AND TYPE II DIABETES: USE CASES
  4. Copyright
  5. Contents
  6. Contributors
  7. Preface
  8. I - Diagnosis
  9. II - Glucose monitoring
  10. III - Prediction of complications and risk stratification
  11. IV - Dialysis
  12. V - Drug design and treatment response
  13. Index
  14. Back Cover