Discriminating Schizophrenia from Normal Controls Using Resting State Functional Network Connectivity: A Deep Neural Network and Layer-Wise Relevance Propagation Method
文献类型：会议论文
| 作者 | 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
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| 出版日期 | 2017 |
| 会议日期 | 2017/9/25-28 |
| 会议地点 | Tokyo,Japan |
| 关键词 | Deep Neural Network Layer-wise Relevance Propagation Functional Network Connectivity Schizophrenia Classification Fmri |
| 英文摘要 | Deep learning has gained considerable attention in the scientific community, breaking benchmark records in many fields such as speech and visual recognition [1]. 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. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20785]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 通讯作者 | Sui Jing(隋婧)(1); Tianzi Jiang |
| 作者单位 | Institute of Automation Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | 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]. 见:. Tokyo,Japan. 2017/9/25-28. |
入库方式： OAI收割
来源：自动化研究所
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