@inproceedings{777accf2a8134905aeb7587101cae62e,
title = "Discriminating bipolar disorder from major depression using whole-brain functional connectivity: A feature selection analysis with SVM-FoBA algorithm",
abstract = "It is known that both bipolar disorder (BD) and major depressive disorder (MDD) indicate depressive symptoms, especially in the early phase of illness. Therefore, discriminating BD from MDD is a major clinical challenge due to the absence of biomarkers. Feature selection is especially important in neuroimaging applications, yet high feature dimensions, low sample size and model understanding present huge challenges. Here we propose an advanced feature selection algorithm, 'SVM-FoBa', which enables adaptive selection of informative feature subsets from high dimensional brain functional connectives (FC) resulted from fMRI. With 38 significant FCs chosen from 6,670 ones, classification accuracy between BD and MDD was achieved up to 88% with leave-one-out cross validation. Further, by conducting weight analysis, the most discriminative FCs were revealed, which adds our understanding on functional deficits and may serve as potential biomarkers for mood disorders.",
keywords = "Functional connectivity, SVM-FoBa, bipolar disorder, feature selection, major depression disorder",
author = "Jie, {Nan Feng} and Osuch, {Elizabeth A.} and Zhu, {Mao Hu} and Ma, {Xiao Ying} and Michael Wammes and Jiang, {Tian Zi} and Jing Sui and Calhoun, {Vince D.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 25th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2015 ; Conference date: 17-09-2015 Through 20-09-2015",
year = "2015",
month = nov,
day = "10",
doi = "10.1109/MLSP.2015.7324352",
language = "English (US)",
series = "IEEE International Workshop on Machine Learning for Signal Processing, MLSP",
publisher = "IEEE Computer Society",
editor = "Deniz Erdogmus and Serdar Kozat and Jan Larsen and Murat Akcakaya",
booktitle = "2015 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2015",
}