@inproceedings{20b5c425b17147babfef76180c9d0370,
title = "Large-scale classification of major depressive disorder via distributed Lasso",
abstract = "Compared to many neurological disorders, for which imaging biomarkers are often available, there are no accepted imaging biomarkers to assist in the diagnosis of major depressive disorder (MDD). One major barrier to understanding MDD has been the lack of a practical and efficient platform for collaborative efforts across multiple data centers; integrating the knowledge from different centers should make it easier to identify characteristic measures that are consistently associated with the illness. Here we applied our newly developed {"}distributed Lasso{"} method to brain MRI data from multiple centers to perform feature selection and classification. Over 1,000 participants were involved in the study; our results indicate the potential of the proposed framework to enable large-scale collaborative data analysis in the future.",
keywords = "Distributed Lasso, ENIGMA",
author = "Dajiang Zhu and Qingyang Li and Riedel, {Brandalyn C.} and Neda Jahanshad and Hibar, {Derrek P.} and Veer, {Ilya M.} and Henrik Walter and Lianne Schmaal and Veltman, {Dick J.} and Dominik Grotegerd and Udo Dannlowski and Sacchet, {Matthew D.} and Gotlib, {Ian H.} and Jieping Ye and Thompson, {Paul M.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; 12th International Symposium on Medical Information Processing and Analysis, SIPAIM 2016 ; Conference date: 05-12-2016 Through 07-12-2016",
year = "2017",
doi = "https://doi.org/10.1117/12.2256935",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Eduardo Romero and Natasha Lepore and Jorge Brieva and Ignacio Larrabide",
booktitle = "12th International Symposium on Medical Information Processing and Analysis",
address = "United States",
}