Big Data in Psychiatry and Neurology
eBook - ePub

Big Data in Psychiatry and Neurology

  1. 384 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Big Data in Psychiatry and Neurology

About this book

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. - Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders - Analyzes methods in using big data to treat psychiatric and neurological disorders - Describes the role machine learning can play in the analysis of big data - Demonstrates the various methods of gathering big data in medicine - Reviews how to apply big data to genetics

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Yes, you can access Big Data in Psychiatry and Neurology by Ahmed Moustafa in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Cognitive Neuroscience & Neuropsychology. 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. Dedication
  7. Contributors
  8. Editor's biography
  9. Preface
  10. Acknowledgment
  11. Chapter 1 Best practices for supervised machine learning when examining biomarkers in clinical populations
  12. Chapter 2 Big data in personalized healthcare
  13. Chapter 3 Longitudinal data analysis: The multiple indicators growth curve model approach
  14. Chapter 4 Challenges and solutions for big data in personalized healthcare
  15. Chapter 5 Data linkages in epidemiology
  16. Chapter 6 Neutrosophic rule-based classification system and its medical applications
  17. Chapter 7 From complex to neural networks
  18. Chapter 8 The use of Big Data in Psychiatry—The role of administrative databases
  19. Chapter 9 Predicting the emergence of novel psychoactive substances with big data
  20. Chapter 10 Hippocampus segmentation in MR images: Multiatlas methods and deep learning methods
  21. Chapter 11 A scalable medication intake monitoring system
  22. Chapter 12 Evaluating cascade prediction via different embedding techniques for disease mitigation
  23. Chapter 13 A two-stage classification framework for epileptic seizure prediction using EEG wavelet-based features
  24. Chapter 14 Visual neuroscience in the age of big data and artificial intelligence
  25. Chapter 15 Application of big data and artificial intelligence approaches in diagnosis and treatment of neuropsychiatric diseases
  26. Chapter 16 Harnessing big data to strengthen evidence-informed precise public health response
  27. Chapter 17 How big data analytics is changing the face of precision medicine in women’s health
  28. Index