Big Data Analytics for Healthcare
eBook - ePub

Big Data Analytics for Healthcare

Datasets, Techniques, Life Cycles, Management, and Applications

  1. 354 pages
  2. English
  3. ePUB (mobile friendly)
  4. Only available on web
eBook - ePub

Big Data Analytics for Healthcare

Datasets, Techniques, Life Cycles, Management, and Applications

Book details
Table of contents
Citations

About This Book

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work.

  • Presents theories, methods and approaches in which data analytic techniques are used for medical data
  • Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases
  • Discusses social, behavioral, and medical fake news analytics for medical information systems

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Yes, you can access Big Data Analytics for Healthcare by Pantea Keikhosrokiani in PDF and/or ePUB format, as well as other popular books in Medicine & Biotechnology in Medicine. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2022
ISBN
9780323985161
Topic
Medicine
Subtopic
Biotechnology in Medicine

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Preface
  7. Section I. Theories and concepts of big data analytics in healthcare
  8. Section II. Big medical data: Techniques, managements, and applications
  9. Section III. Diagnosis and treatment: Big data analytical techniques, datasets, life cycles, managements, and applications for diagnosis and treatment
  10. Section IV. Prediction: Big data analytical techniques, datasets, life cycles, managements, and applications for prediction
  11. Section V. Big medical fake news analytics for preventing medical misinformation and myths
  12. Section VI. Challenges and future of big data in healthcare
  13. Section VII. Case studies of big data in healthcare arena
  14. Index