The impact of machine learning techniques in the study of bipolar disorder: A systematic review-Reference-Cited by-同舟云学术

The impact of machine learning techniques in the study of bipolar disorder: A systematic review

Published:2017-09 Issue: Volume:80 Page:538-554
ISSN:0149-7634
Container-title:Neuroscience & Biobehavioral Reviews
language:en
Short-container-title:Neuroscience & Biobehavioral Reviews

Author:

Librenza-Garcia Diego,Kotzian Bruno Jaskulski,Yang Jessica,Mwangi Benson,Cao Bo,Pereira Lima Luiza Nunes,Bermudez Mariane Bagatin,Boeira Manuela Vianna,Kapczinski Flávio,Passos Ives Cavalcante

Funder

Cilag

Eli Lilly and Company

National Alliance for Research on Schizophrenia and Depression

Servier

Stanley Medical Research Institute

Publisher

Elsevier BV

Subject

Behavioral Neuroscience,Cognitive Neuroscience,Neuropsychology and Physiological Psychology

Reference79 articles.

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3. Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity;Almeida;Br. J. Psychiatry,2013

4. Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness;Anticevic;Cereb. Cortex,2014

5. Automatic bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from fMRI data;Arribas;IEEE Trans. Biomed. Eng.,2010

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