Discriminating bipolar disorder from major depression using whole-brain functional connectivity: A feature selection analysis with SVM-FoBA algorithm

@article{Jie2015DiscriminatingBD,
  title={Discriminating bipolar disorder from major depression using whole-brain functional connectivity: A feature selection analysis with SVM-FoBA algorithm},
  author={Nan-Feng Jie and Elizabeth A. Osuch and Mao-Hu Zhu and Michael Wammes and Xiao-Ying Ma and Tianzi Jiang and Jing Sui and Vince D. Calhoun},
  journal={2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)},
  year={2015},
  pages={1-6}
}
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… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 41 references

Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.

Proceedings of the National Academy of Sciences of the United States of America • 1999
View 8 Excerpts
Highly Influenced

Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

IEEE Transactions on Neural Systems and Rehabilitation Engineering • 2014
View 5 Excerpts
Highly Influenced

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