Personalized Psychiatry : Big Data Analytics in Mental Health

This book integrates the concepts of big data analytics into mental health practice and research. Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years l...

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Corporate Author: SpringerLink (Online service)
Other Authors: Passos, Ives Cavalcante (Editor), Mwangi, Benson (Editor), Kapczinski, Flávio (Editor)
Format: eBook
Published: Cham Springer International Publishing 2019, 2019
Edition:1st ed. 2019
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 1. Big data and Machine Learning Techniques Meet Health Sciences
  • 2. Major challenges and limitations of Big data analytics
  • 3. A Clinical Perspective on Big Data in Mental Health
  • 4. Big Data Guided Interventions: Predicting Treatment Response
  • 5. The role of big data analytics in predicting suicide
  • 6. Emerging Shifts in Neuroimaging Data Analysis in the Era of “Big Data"
  • 7. Phenomapping: methods and measures for deconstructing diagnosis in psychiatry
  • 8. How to integrate data from multiple biological layers in mental health?
  • 9. Ethics in the Era of Big Data