Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force

Ives C. Passos, Pedro L. Ballester, Rodrigo C. Barros, Diego Librenza-Garcia, Benson Mwangi, Boris Birmaher, Elisa Brietzke, Tomas Hajek, Carlos Lopez Jaramillo, Rodrigo B. Mansur, Martin Alda, Bartholomeus C. M. Haarman, Erkki Isometsa, Raymond W. Lam, Roger S. McIntyre, Luciano Minuzzi, Lars V. Kessing, Lakshmi N. Yatham, Anne Duffy, Flavio Kapczinski

Research output: Contribution to journalReview ArticleScientificpeer-review

Original languageEnglish
JournalBipolar Disorders
Volume21
Issue number7
Pages (from-to)582-594
Number of pages13
ISSN1398-5647
DOIs
Publication statusPublished - Nov 2019
MoE publication typeA2 Review article in a scientific journal

Fields of Science

  • big data
  • bipolar disorder
  • data mining
  • deep learning
  • machine learning
  • personalized psychiatry
  • predictive psychiatry
  • risk prediction
  • MOOD DISORDERS
  • PREDICTING SUICIDALITY
  • LITHIUM RESPONSE
  • RISK
  • DEPRESSION
  • SCHIZOPHRENIA
  • ASSOCIATION
  • CLASSIFICATION
  • SYMPTOMS
  • NEUROPROGRESSION
  • 3112 Neurosciences
  • 3124 Neurology and psychiatry

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