摘要
大量研究表明轻微肝性脑病(MHE)与脑功能网络的异常相关,但难于寻找与MHE相关的异常子网络.为了解决这个问题,文中提出判别性子图重构的方法用于寻找与MHE相关的子网络,并将子网络用于MHE的分类.首先分别从MHE病人和非MHE(NMHE)病人的功能网络中挖掘一组频繁子图.然后,从频繁子图中挑选判别性子图用于重构原网络,并将判别性子图合并用于重构原网络.最后,使用图核计算重构网络之间的相似性,并使用核SVM分类.在包括77位肝硬化病人的数据集上的实验获得较高的分类精度,从而验证方法的有效性.
Minimal hepatic encephalopathy ( MHE) is related to the abnormality of subnetworks, but searching related subnetworks is still a challenging task. To solve this problem, a method based on discriminative subgraph reconstruction is proposed to search subnetworks related to MHE and the subnetworks are used for MHE classification. Firstly, frequent subgraphs are mined from the functional connectivity networks of MHE and non-MHE (NMHE), respectively. Next, the discriminative subgraphs are selected from the frequent subgraphs for the original networks reconstruction and the combination of discriminative networks is conducted to reconstruct the original networks. Finally, the graph kernel is applied to compute the similarity between pairwise reconstructed networks and the kernel SVM is adopted for MHE classification. On the dataset of 77 patients with hepatic cirrhosis, the high accuracy of the proposed algorithm is achieved and the effectiveness of the proposed method is demonstrated.
作者
屠黎阳
杜俊强
接标
张道强
TU Liyang DU Junqiang JIE Biao ZHANG Daoqiang(College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106 School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241000)
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2016年第9期832-839,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61422204
61473149)
江苏省杰出青年自然科学基金项目(No.BK20130034)
江苏省研究生培养创新工程(No.SJLX15_0140)资助~~
关键词
肝性脑病
判别性子图
子图重构
图核
Hepatic Encephalopathy
Discriminative Subgraph
Subgraph Reconstruction
Graph Kernel