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. Available on iOS & Android
eBook - ePub

Big Data Analytics for Healthcare

Datasets, Techniques, Life Cycles, Management, and Applications

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 & Pharmaceutical, Biotechnology & Healthcare Industry. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Big Data Analytics for Healthcare
  2. Chapter 1 Big data analytics in healthcare
  3. Chapter 2 Driving impact through big data utilization and analytics in the context of a Learning Health System
  4. Chapter 3 Classification of medical big data
  5. Chapter 4 Towards big data framework in government public open data (GPOD) for health
  6. Chapter 5 Big data analytics techniques for healthcare
  7. Chapter 6 Big data analytics in precision medicine
  8. Chapter 7 Recent advances in processing, interpreting, and managing biological data for therapeutic intervention of human infectious disease
  9. Chapter 8 Big data analytics for health
  10. Chapter 9 Recent applications of data mining in medical diagnosis and prediction
  11. Chapter 10 Big medical data analytics for diagnosis
  12. Chapter 11 Big data analytics and radiomics to discover diagnostics on different cancer types
  13. Chapter 12 Big medical data, cloud computing, and artificial intelligence for improving diagnosis in healthcare
  14. Chapter 13 Use of artificial intelligence for predicting infectious disease
  15. Chapter 14 Hospital data analytics system for tracking and predicting obese patients' lifestyle habits
  16. Chapter 15 Predictions on diabetic patient datasets using big data analytics and machine learning techniques
  17. Chapter 16 Skin cancer prediction using big data analytics and AI techniques
  18. Chapter 17 COVID-19 fake news analytics from social media using topic modeling and clustering
  19. Chapter 18 Big medical data mining system (BigMed) for the detection and classification of COVID-19 misinformation
  20. Chapter 19 Privacy security risks of big data processing in healthcare
  21. Chapter 20 Opportunities and challenges in healthcare with the management of big biomedical data
  22. Chapter 21 Future direction for healthcare based on big data analytics
  23. Chapter 22 Big data in orthopedics
  24. Chapter 23 Predicting onset (type-2) of diabetes from medical records using binary class classification
  25. Chapter 24 Screening programs incorporating big data analytics
  26. Index