@article{cdbde6b09d464a90902f12ba78471878,
title = "Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force",
keywords = "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",
author = "Passos, {Ives C.} and Ballester, {Pedro L.} and Barros, {Rodrigo C.} and Diego Librenza-Garcia and Benson Mwangi and Boris Birmaher and Elisa Brietzke and Tomas Hajek and {Lopez Jaramillo}, Carlos and Mansur, {Rodrigo B.} and Martin Alda and Haarman, {Bartholomeus C. M.} and Erkki Isometsa and Lam, {Raymond W.} and McIntyre, {Roger S.} and Luciano Minuzzi and Kessing, {Lars V.} and Yatham, {Lakshmi N.} and Anne Duffy and Flavio Kapczinski",
year = "2019",
month = nov,
doi = "10.1111/bdi.12828",
language = "English",
volume = "21",
pages = "582--594",
journal = "Bipolar Disorders",
issn = "1398-5647",
publisher = "Wiley",
number = "7",
}