Accepted Manuscript Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach Juliana M. Sartori, Ramiro Reckziegel, Ives Cavalcante Passos, Leticia S. Czepielewski, Adam Fijtman, Leonardo A. Sodré, Raffael Massuda, Pedro D. Goi, Miréia Vianna-Sulzbach, Taiane de Azevedo Cardoso, Flávio Kapczinksi, Benson Mwangi, Clarissa S. Gama PII: S0022-3956(18)30025-6 DOI: 10.1016/j.jpsychires.2018.05.023 Reference: PIAT 3387 To appear in: Journal of Psychiatric Research Received Date: 17 January 2018 Revised Date: 30 April 2018 Accepted Date: 24 May 2018 Please cite this article as: Sartori JM, Reckziegel R, Passos IC, Czepielewski LS, Fijtman A, Sodré LA, Massuda R, Goi PD, Vianna-Sulzbach Miré., Cardoso TdA, Kapczinksi Flá., Mwangi B, Gama CS, Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach, Journal of Psychiatric Research (2018), doi: 10.1016/j.jpsychires.2018.05.023. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.