| Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls MR Arbabshirani, S Plis, J Sui, VD Calhoun Neuroimage 145, 137-165, 2017 | 869 | 2017 |
| A review of multivariate methods for multimodal fusion of brain imaging data J Sui, T Adali, Q Yu, J Chen, VD Calhoun Journal of neuroscience methods 204 (1), 68-81, 2012 | 408 | 2012 |
| Multimodal fusion of brain imaging data: a key to finding the missing link (s) in complex mental illness VD Calhoun, J Sui Biological psychiatry: cognitive neuroscience and neuroimaging 1 (3), 230-244, 2016 | 407 | 2016 |
| Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder VD Calhoun, J Sui, K Kiehl, J Turner, E Allen, G Pearlson Frontiers in Psychiatry 2, 75, 2012 | 266 | 2012 |
| Machine learning in major depression: From classification to treatment outcome prediction S Gao, VD Calhoun, J Sui CNS neuroscience & therapeutics 24 (11), 1037-1052, 2018 | 263 | 2018 |
| Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model J Sui, G Pearlson, A Caprihan, T Adali, KA Kiehl, J Liu, J Yamamoto, ... Neuroimage 57 (3), 839-855, 2011 | 262 | 2011 |
| A hybrid machine learning method for fusing fMRI and genetic data: combining both improves classification of schizophrenia H Yang, J Liu, J Sui, G Pearlson, VD Calhoun Frontiers in human neuroscience 4, 192, 2010 | 240 | 2010 |
| Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia Q Yu, EB Erhardt, J Sui, Y Du, H He, D Hjelm, MS Cetin, S Rachakonda, ... Neuroimage 107, 345-355, 2015 | 235 | 2015 |
| Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises J Sui, R Jiang, J Bustillo, V Calhoun Biological psychiatry 88 (11), 818-828, 2020 | 231 | 2020 |
| Interaction among subsystems within default mode network diminished in schizophrenia patients: a dynamic connectivity approach Y Du, GD Pearlson, Q Yu, H He, D Lin, J Sui, L Wu, VD Calhoun Schizophrenia research 170 (1), 55-65, 2016 | 216 | 2016 |
| NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders Y Du, Z Fu, J Sui, S Gao, Y Xing, D Lin, M Salman, A Abrol, MA Rahaman, ... NeuroImage: Clinical 28, 102375, 2020 | 213 | 2020 |
| In search of multimodal neuroimaging biomarkers of cognitive deficits in schizophrenia J Sui, GD Pearlson, Y Du, Q Yu, TR Jones, J Chen, T Jiang, J Bustillo, ... Biological psychiatry 78 (11), 794-804, 2015 | 176 | 2015 |
| Function–structure associations of the brain: evidence from multimodal connectivity and covariance studies J Sui, R Huster, Q Yu, JM Segall, VD Calhoun Neuroimage 102, 11-23, 2014 | 173 | 2014 |
| Brain connectivity networks in schizophrenia underlying resting state functional magnetic resonance imaging Q Yu, E A Allen, J Sui, M R Arbabshirani, G Pearlson, V D Calhoun Current topics in medicinal chemistry 12 (21), 2415-2425, 2012 | 161 | 2012 |
| Distinct and common aspects of physical and psychological self-representation in the brain: A meta-analysis of self-bias in facial and self-referential judgements C Hu, X Di, SB Eickhoff, M Zhang, K Peng, H Guo, J Sui Neuroscience & biobehavioral reviews 61, 197-207, 2016 | 160 | 2016 |
| Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study Q Yu, J Sui, S Rachakonda, H He, W Gruner, G Pearlson, KA Kiehl, ... PloS one 6 (9), e25423, 2011 | 158 | 2011 |
| Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion J Sui, S Qi, TGM van Erp, J Bustillo, R Jiang, D Lin, JA Turner, ... Nature communications 9 (1), 3028, 2018 | 145 | 2018 |
| Three-Way (N-way) fusion of brain imaging data based on mCCA+ jICA and its application to discriminating schizophrenia J Sui, H He, GD Pearlson, T Adali, KA Kiehl, Q Yu, VP Clark, E Castro, ... NeuroImage, 2012 | 137 | 2012 |
| A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders Y Du, GD Pearlson, J Liu, J Sui, Q Yu, H He, E Castro, VD Calhoun Neuroimage 122, 272-280, 2015 | 135 | 2015 |
| An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques J Sui, T Adali, GD Pearlson, VD Calhoun Neuroimage 46 (1), 73-86, 2009 | 129 | 2009 |
Vince D. CalhounDirector-Translational Research in Neuroimaging and Data Science (TReNDS;GSU/GAtech/Emory)Verified email at gsu.edu
