|Discriminating Schizophrenia from Normal Controls Using Resting State Functional Network Connectivity: A Deep Neural Network and Layer-Wise Relevance Propagation Method|
|Weizheng Yan; Sergey Plis; Vince D Calhoun; Shengfeng Liu; Rongtao Jiang; Tian-Zi Jiang; Sui Jing(隋婧); Sui Jing(隋婧)(1); Tianzi Jiang
|Conference Name||2017 IEEE International Workshop on Machine Learning for Signal Processing(MLSP)
|Abstract||Deep learning has gained considerable attention in the scientific community, breaking benchmark records in many fields such as speech and visual recognition . Motivated by extending advancement of deep learning approaches to brain imaging classification, we propose a framework, called "deep neural network (DNN)+ layer-wise relevance propagation (LRP)", to distinguish schizophrenia patients (SZ) from healthy controls (HCs) using functional network connectivity (FNC). 1100 Chinese subjects of 7 sites are included, each with a 50*50 FNC matrix resulted from group ICA on resting-state fMRI data. The proposed DNN+LRP not only improves classification accuracy significantly compare to four state-of-the-art classification methods (84% vs. less than 79%, 10 folds cross validation) but also enables identification of the most contributing FNC patterns related to SZ classification, which cannot be easily traced back by general DNN models. By conducting LRP, we identified the FNC patterns that exhibit the highest discriminative power in SZ classification. More importantly, when using leave-one-site-out cross validation (using 6 sites for training, 1 site for testing, 7 times in total), the cross-site classification accuracy reached 82%, suggesting high robustness and generalization performance of the proposed method, promising a wide utility in the community and great potentials for biomarker identification of brain disorders.|
|Keyword||Deep Neural Network
Layer-wise Relevance Propagation
Functional Network Connectivity
|Corresponding Author||Sui Jing(隋婧)(1); Tianzi Jiang|
|Affiliation||Institute of Automation Chinese Academy of Sciences|
Weizheng Yan,Sergey Plis,Vince D Calhoun,et al. Discriminating Schizophrenia from Normal Controls Using Resting State Functional Network Connectivity: A Deep Neural Network and Layer-Wise Relevance Propagation Method[C],2017.
|Files in This Item:||
||There are no files associated with this item.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.