2023
Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study
Meng X, Iraji A, Fu Z, Kochunov P, Belger A, Ford J, McEwen S, Mathalon D, Mueller B, Pearlson G, Potkin S, Preda A, Turner J, van Erp T, Sui J, Calhoun V. Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study. NeuroImage Clinical 2023, 38: 103434. PMID: 37209635, PMCID: PMC10209454, DOI: 10.1016/j.nicl.2023.103434.Peer-Reviewed Original ResearchConceptsIndependent component analysisData-driven approachData miningF1 scoreClassification modelReference algorithmNetwork connectivityMagnetic resonance imaging dataNetworkImaging dataPredictive resultsPatient dataFunctional magnetic resonance imaging (fMRI) dataData acquisition timeConnectivity networksFrameworkConnectivityPromising approachNew subjectMiningAnalytic approachAlgorithmDatasetAcquisition timeComponent analysis
2012
Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia
Sui J, He H, Liu J, Yu Q, Adali T, Pearlson G, Calhoun V. Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2012, 2012: 2692-2695. PMID: 23366480, DOI: 10.1109/embc.2012.6346519.Peer-Reviewed Original ResearchConceptsMulti-set canonical correlation analysisData fusionMulti-modal fusionDisparate data setsMultiple data typesJoint independent component analysisData typesFusion modelJoint informationData setsIndependent component analysisHigher decomposition accuracyEffective mannerCanonical correlation analysisDecomposition accuracyLimited viewEffective approachPromising approachBiomedical imagingFusionComponent analysisAccuracyIllness biomarkersInformationSet