Citation: | Lu SHEN, Qianting WANG, Jun SHI. Single-modal neuroimaging computer aided diagnosis for schizophrenia based on ensemble learning using privileged information[J]. JOURNAL OF MECHANICAL ENGINEERING, 2020, 37(3): 405-411, 418. doi: 10.7507/1001-5515.201905029 |
[1] |
管丽丽, 杜立哲, 马弘. 精神分裂症的疾病负担. 中国心理卫生杂志, 2012, 26(12): 913-919. doi: 10.3969/j.issn.1000-6729.2012.12.008
|
[2] |
Birur B, Kraguljac N V, Shelton R C, et al. Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature. NPJ Schizophrenia, 2017, 3(1): 15. doi: 10.1038/s41537-017-0013-9
|
[3] |
Shi Jun, Zheng Xiao, Li Yan, et al. Multimodal neuroimaging feature learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer’s disease. IEEE J Biomed Health Inform, 2018, 22(1): 173-183. doi: 10.1109/JBHI.2017.2655720
|
[4] |
Shi Jun, Xue Zeyu, Dai Yakang, et al. Cascaded multi-column RVFL+ classifier for single-modal neuroimaging-based diagnosis of Parkinson’s disease. IEEE Trans Biomed Eng, 2019, 66(8): 2362-2371. doi: 10.1109/TBME.2018.2889398
|
[5] |
Kasun L L C, Zhou H, Huang G B, et al. Representational learning with extreme learning machine for big data. IEEE Intell Syst, 2013, 28(6): 31-34.
|
[6] |
Tang Jiexiong, Deng Chenwei, Huang Guangbin. Extreme learning machine for multilayer perceptron. IEEE Trans Neural Netw Learn Syst, 2016, 27(4): 809-821. doi: 10.1109/TNNLS.2015.2424995
|
[7] |
Zhang Junjie, Yin Jie, Zhang Qi, et al. Robust sound event classification with bilinear multi-column ELM-AE and two-stage ensemble learning. EURASIP Journal on Audio, Speech, and Music Processing, 2017: 11.
|
[8] |
Vapnik V, Vashist A. A new learning paradigm: learning using privileged information. Neural Netw, 2009, 22(5/6): 544-557.
|
[9] |
Duan Lixin, Xu Yanwu, Li Wen, et al. Incorporating privileged genetic information for fundus image based glaucoma detection// International Conference on Medical Image Computing and Computer-Assisted Intervention. Boston: Springer, 2014: 204-211.
|
[10] |
Zheng Xiao, Shi Jun, Ying Shihui, et al. Improving single-modal neuroimaging based diagnosis of brain disorders via boosted privileged information learning framework// International Workshop on Machine Learning in Medical Imaging. Athens: Springer, 2016: 95-103.
|
[11] |
Zheng X, Shi J, Zhang Q, et al. Improving MRI-based diagnosis of Alzheimer’s disease via an ensemble privileged information learning algorithm// 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne: IEEE, 2017: 456-459.
|
[12] |
Huang Guangbin, Zhu Qinyu, Siew C K. Extreme learning machine: Theory and applications. Neurocomputing, 2006, 70(1/3): 489-501.
|
[13] |
Zhu P F, Zhang L, Hu Q H, et al. Multi-scale patch based collaborative representation for face recognition with margin distribution optimization// European Conference on Computer Vision. Firenze: Springer, 2012: 822-835.
|
[14] |
Yang Fan, Lu Huchuan, Yang M H. Robust visual tracking via multiple kernel boosting with affinity constraints. IEEE Transactions on Circuits and Systems for Video Technology, 2014, 24(2): 242-254. doi: 10.1109/TCSVT.2013.2276145
|
[15] |
Xu Lai, Groth K M, Pearlson G, et al. Source-based morphometry: the use of independent component analysis to identify gray matter differences with application to schizophrenia. Hum Brain Mapp, 2009, 30(3): 711-724. doi: 10.1002/hbm.20540
|
[16] |
Jafri M J, Pearlson G D, Stevens M, et al. A method for functional network connectivity among spatially independent resting-state components in schizophrenia. Neuroimage, 2008, 39(4): 1666-1681. doi: 10.1016/j.neuroimage.2007.11.001
|
[17] |
Esposito F, Scarabino T, Hyvarinen A, et al. Independent component analysis of fMRI group studies by self-organizing clustering. Neuroimage, 2005, 25(1): 193-205. doi: 10.1016/j.neuroimage.2004.10.042
|
[18] |
Hyvärinen A, Oja E. Independent component analysis: algorithms and applications. Neural Netw, 2000, 13(4/5): 411-430.
|
[19] |
Calhoun V D, Adali T, Pearlson G D, et al. A method for making group inferences from functional MRI data using independent component analysis. Hum Brain Mapp, 2001, 14(3): 140-151. doi: 10.1002/hbm.1048
|
[20] |
Silva R F, Castro E, Gupta C N, et al. The tenth annual MLSP competition: Schizophrenia classification challenge// 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). Reims: IEEE, 2014: 1-6.
|