157 related articles for article (PubMed ID: 19761569)
1. Feature selection for fMRI-based deception detection.
Jin B; Strasburger A; Laken SJ; Kozel FA; Johnson KA; George MS; Lu X
BMC Bioinformatics; 2009 Sep; 10 Suppl 9(Suppl 9):S15. PubMed ID: 19761569
[TBL] [Abstract][Full Text] [Related]
2. Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns.
De Martino F; Valente G; Staeren N; Ashburner J; Goebel R; Formisano E
Neuroimage; 2008 Oct; 43(1):44-58. PubMed ID: 18672070
[TBL] [Abstract][Full Text] [Related]
3. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.
Vu H; Kim HC; Jung M; Lee JH
Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633
[TBL] [Abstract][Full Text] [Related]
4. Lying in the scanner: covert countermeasures disrupt deception detection by functional magnetic resonance imaging.
Ganis G; Rosenfeld JP; Meixner J; Kievit RA; Schendan HE
Neuroimage; 2011 Mar; 55(1):312-9. PubMed ID: 21111834
[TBL] [Abstract][Full Text] [Related]
5. Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.
Guo H; Li Y; Mensah GK; Xu Y; Chen J; Xiang J; Chen D
Comput Math Methods Med; 2019; 2019():9108108. PubMed ID: 31781290
[TBL] [Abstract][Full Text] [Related]
6. A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: application to schizophrenia.
Castro E; Gómez-Verdejo V; Martínez-Ramón M; Kiehl KA; Calhoun VD
Neuroimage; 2014 Feb; 87():1-17. PubMed ID: 24225489
[TBL] [Abstract][Full Text] [Related]
7. Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models.
Faisan S; Thoraval L; Armspach JP; Metz-Lutz MN; Heitz F
IEEE Trans Med Imaging; 2005 Feb; 24(2):263-76. PubMed ID: 15707252
[TBL] [Abstract][Full Text] [Related]
8. Classifying spatial patterns of brain activity with machine learning methods: application to lie detection.
Davatzikos C; Ruparel K; Fan Y; Shen DG; Acharyya M; Loughead JW; Gur RC; Langleben DD
Neuroimage; 2005 Nov; 28(3):663-8. PubMed ID: 16169252
[TBL] [Abstract][Full Text] [Related]
9. Multivoxel pattern analysis for FMRI data: a review.
Mahmoudi A; Takerkart S; Regragui F; Boussaoud D; Brovelli A
Comput Math Methods Med; 2012; 2012():961257. PubMed ID: 23401720
[TBL] [Abstract][Full Text] [Related]
10. Classification of autistic individuals and controls using cross-task characterization of fMRI activity.
Chanel G; Pichon S; Conty L; Berthoz S; Chevallier C; Grèzes J
Neuroimage Clin; 2016; 10():78-88. PubMed ID: 26793434
[TBL] [Abstract][Full Text] [Related]
11. A hybrid method for classifying cognitive states from fMRI data.
Parida S; Dehuri S; Cho SB; Cacha LA; Poznanski RR
J Integr Neurosci; 2015 Sep; 14(3):355-68. PubMed ID: 26455882
[TBL] [Abstract][Full Text] [Related]
12. Support vector clustering for brain activation detection.
Wang D; Shi L; Yeung DS; Heng PA; Wong TT; Tsang EC
Med Image Comput Comput Assist Interv; 2005; 8(Pt 1):572-9. PubMed ID: 16685892
[TBL] [Abstract][Full Text] [Related]
13. Multi-subject brain decoding with multi-task feature selection.
Wang L; Tang X; Liu W; Peng Y; Gao T; Xu Y
Biomed Mater Eng; 2014; 24(6):2987-94. PubMed ID: 25227006
[TBL] [Abstract][Full Text] [Related]
14. Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.
Faisan S; Thoraval L; Armspach JP; Foucher JR; Metz-Lutz MN; Heitz F
Acad Radiol; 2005 Jan; 12(1):25-36. PubMed ID: 15691723
[TBL] [Abstract][Full Text] [Related]
15. Interpretable whole-brain prediction analysis with GraphNet.
Grosenick L; Klingenberg B; Katovich K; Knutson B; Taylor JE
Neuroimage; 2013 May; 72():304-21. PubMed ID: 23298747
[TBL] [Abstract][Full Text] [Related]
16. Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI.
Shen H; Wang L; Liu Y; Hu D
Neuroimage; 2010 Feb; 49(4):3110-21. PubMed ID: 19931396
[TBL] [Abstract][Full Text] [Related]
17. Detecting stable distributed patterns of brain activation using Gini contrast.
Langs G; Menze BH; Lashkari D; Golland P
Neuroimage; 2011 May; 56(2):497-507. PubMed ID: 20709176
[TBL] [Abstract][Full Text] [Related]
18. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.
Douglas PK; Harris S; Yuille A; Cohen MS
Neuroimage; 2011 May; 56(2):544-53. PubMed ID: 21073969
[TBL] [Abstract][Full Text] [Related]
19. Automated classification of fMRI data employing trial-based imagery tasks.
Lee JH; Marzelli M; Jolesz FA; Yoo SS
Med Image Anal; 2009 Jun; 13(3):392-404. PubMed ID: 19233711
[TBL] [Abstract][Full Text] [Related]
20. Characterization of groups using composite kernels and multi-source fMRI analysis data: application to schizophrenia.
Castro E; Martínez-Ramón M; Pearlson G; Sui J; Calhoun VD
Neuroimage; 2011 Sep; 58(2):526-36. PubMed ID: 21723948
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
