{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T22:29:47Z","timestamp":1792448987605,"version":"4.5.0"},"reference-count":464,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T00:00:00Z","timestamp":1588723200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01EB020407"],"award-info":[{"award-number":["1R01EB020407"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01MH118695"],"award-info":[{"award-number":["1R01MH118695"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Human Brain Mapping"],"published-print":{"date-parts":[[2020,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Neuroimaging\u2010based approaches have been extensively applied to study mental illness in recent years and have deepened our understanding of both cognitively healthy and disordered brain structure and function. Recent advancements in machine learning techniques have shown promising outcomes for individualized prediction and characterization of patients with psychiatric disorders. Studies have utilized features from a variety of neuroimaging modalities, including structural, functional, and diffusion magnetic resonance imaging data, as well as jointly estimated features from multiple modalities, to assess patients with heterogeneous mental disorders, such as schizophrenia and autism. We use the term \u201cpredictome\u201d to describe the use of multivariate brain network features from one or more neuroimaging modalities to predict mental illness. In the predictome, multiple brain network\u2010based features (either from the same modality or multiple modalities) are incorporated into a predictive model to jointly estimate features that are unique to a disorder and predict subjects accordingly. To date, more than 650 studies have been published on subject\u2010level prediction focusing on psychiatric disorders. We have surveyed about 250 studies including schizophrenia, major depression, bipolar disorder, autism spectrum disorder, attention\u2010deficit hyperactivity disorder, obsessive\u2013compulsive disorder, social anxiety disorder, posttraumatic stress disorder, and substance dependence. In this review, we present a comprehensive review of recent neuroimaging\u2010based predictomic approaches, current trends, and common shortcomings and share our vision for future directions.<\/jats:p>","DOI":"10.1002\/hbm.25013","type":"journal-article","created":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T09:09:23Z","timestamp":1588756163000},"page":"3468-3535","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":163,"title":["Towards a brain\u2010based predictome of mental illness"],"prefix":"10.1002","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3602-5109","authenticated-orcid":false,"given":"Barnaly","family":"Rashid","sequence":"first","affiliation":[{"name":"Department of Psychiatry Harvard Medical School  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vince","family":"Calhoun","sequence":"additional","affiliation":[{"name":"Tri\u2010Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, and Emory University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,5,6]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.10.045"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2017.00624"},{"key":"e_1_2_13_4_1","unstructured":"Ad\u2010Dab'bagh Y. Lyttelton O. Muehlboeck J. Lepage C. Einarson D. Mok K. \u2026Fombonne E.(2006).The CIVET image\u2010processing environment: a fully automated comprehensive pipeline for anatomical neuroimaging research. Paper presented at the Proceedings of the 12th annual meeting of the organization for human brain mapping."},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004583-200403000-00018"},{"key":"e_1_2_13_6_1","unstructured":"Alain G. &Bengio Y.(2016). Understanding intermediate layers using linear classifier probes.arXiv preprint arXiv:1610.01644."},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1525-1497.2004.30091.x"},{"key":"e_1_2_13_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhs352"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2011.00002"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2013.00520"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.12.015"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awr263"},{"key":"e_1_2_13_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.10.019"},{"key":"e_1_2_13_14_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bht165"},{"key":"e_1_2_13_15_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2013.00133"},{"key":"e_1_2_13_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.02.079"},{"key":"e_1_2_13_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20995"},{"key":"e_1_2_13_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2010.2080679"},{"key":"e_1_2_13_19_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/16.5.412"},{"key":"e_1_2_13_20_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0050698"},{"key":"e_1_2_13_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.10.002"},{"key":"e_1_2_13_22_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbr125"},{"key":"e_1_2_13_23_1","unstructured":"Bengio Y.(2012).Deep learning of representations for unsupervised and transfer learning. Paper presented at the Proceedings of ICML Workshop on Unsupervised and Transfer Learning."},{"key":"e_1_2_13_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2017.11.017"},{"key":"e_1_2_13_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2016.02.018"},{"key":"e_1_2_13_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-018-9366-0"},{"key":"e_1_2_13_27_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0020151"},{"key":"e_1_2_13_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-45528-0"},{"key":"e_1_2_13_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910340409"},{"key":"e_1_2_13_30_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0911855107"},{"key":"e_1_2_13_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2014.10.033"},{"key":"e_1_2_13_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00063-5"},{"key":"e_1_2_13_33_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00078"},{"key":"e_1_2_13_34_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_2_13_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2013.11.002"},{"key":"e_1_2_13_36_1","doi-asserted-by":"crossref","unstructured":"Brodersen K. H. Ong C. S. Stephan K. E. &Buhmann J. M.(2010).The balanced accuracy and its posterior distribution. Paper presented at the 2010 20th International Conference on Pattern Recognition.","DOI":"10.1109\/ICPR.2010.764"},{"key":"e_1_2_13_37_1","unstructured":"Buccigrossi R. Ellisman M. Grethe J. Haselgrove C. Kennedy D. Martone M. \u2026Turner J. (2008).The Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). Paper presented at the AMIA Annual Symposium proceedings. AMIA Symposium."},{"key":"e_1_2_13_38_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2017.36"},{"key":"e_1_2_13_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2017.11.007"},{"key":"e_1_2_13_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2006.07.006"},{"key":"e_1_2_13_41_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbw053"},{"key":"e_1_2_13_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.08.070"},{"key":"e_1_2_13_43_1","unstructured":"Calhoun V. Adali T. Pearlson G. &Pekar J.(2001a).Group ICA of functional MRI data: Separability stationarity and inference. Paper presented at the Proceedings of the International Conference on ICA and BSS San Diego CA."},{"key":"e_1_2_13_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2008.923773"},{"key":"e_1_2_13_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2012.2211076"},{"key":"e_1_2_13_46_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20204"},{"key":"e_1_2_13_47_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.1048"},{"key":"e_1_2_13_48_1","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780199844180.003.0012"},{"key":"e_1_2_13_49_1","doi-asserted-by":"publisher","DOI":"10.3389\/neuro.09.017.2009"},{"key":"e_1_2_13_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2004.01.011"},{"key":"e_1_2_13_51_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20463"},{"key":"e_1_2_13_52_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2014.10.015"},{"key":"e_1_2_13_53_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2015.12.005"},{"key":"e_1_2_13_54_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-018-0106-5"},{"key":"e_1_2_13_55_1","doi-asserted-by":"publisher","DOI":"10.1186\/1755-8794-6-S3-S2"},{"key":"e_1_2_13_56_1","doi-asserted-by":"publisher","DOI":"10.1111\/pcn.12106"},{"key":"e_1_2_13_57_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.04.255"},{"key":"e_1_2_13_58_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbu016"},{"key":"e_1_2_13_59_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2018.03.001"},{"key":"e_1_2_13_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00702-011-0693-7"},{"key":"e_1_2_13_61_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.10.065"},{"key":"e_1_2_13_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2527717"},{"key":"e_1_2_13_63_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.06.044"},{"key":"e_1_2_13_64_1","doi-asserted-by":"crossref","unstructured":"Castro E. Ulloa A. Plis S. Turner J. &Calhoun V..Simulation of structural magnetic resonance images for deep learning pre\u2010training. Paper presented at the IEEE International Symposium on Biomedical Imaging August2015.","DOI":"10.1109\/ISBI.2015.7164053"},{"key":"e_1_2_13_65_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00466"},{"key":"e_1_2_13_66_1","first-page":"95","article-title":"Enhanced disease characterization through multi network functional normalization in fMRI","volume":"9","author":"\u00c7etin M. S.","year":"2015","journal-title":"Frontiers in Neuroscience"},{"key":"e_1_2_13_67_1","doi-asserted-by":"publisher","DOI":"10.1111\/acps.12824"},{"key":"e_1_2_13_68_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2015.11.010"},{"key":"e_1_2_13_69_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.12.011"},{"key":"e_1_2_13_70_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00066"},{"key":"e_1_2_13_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2015.04.002"},{"key":"e_1_2_13_72_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnpbp.2015.06.014"},{"key":"e_1_2_13_73_1","doi-asserted-by":"publisher","DOI":"10.1002\/aur.1834"},{"key":"e_1_2_13_74_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2015.08.011"},{"key":"e_1_2_13_75_1","doi-asserted-by":"publisher","DOI":"10.1038\/npjschz.2015.16"},{"key":"e_1_2_13_76_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-32290-9"},{"key":"e_1_2_13_77_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.11.066"},{"key":"e_1_2_13_78_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2015.04.002"},{"key":"e_1_2_13_79_1","doi-asserted-by":"crossref","unstructured":"Cicek G. Akan A. &Metin B.(2018).Detection of Attention Deficit Hyperactivity Disorder Using Local and Global Features. Paper presented at the 2018 Medical Technologies National Congress (TIPTEKNO).","DOI":"10.1109\/TIPTEKNO.2018.8597017"},{"key":"e_1_2_13_80_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2015.14091200"},{"key":"e_1_2_13_81_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00059"},{"key":"e_1_2_13_82_1","doi-asserted-by":"publisher","DOI":"10.1111\/adb.12418"},{"key":"e_1_2_13_83_1","doi-asserted-by":"publisher","DOI":"10.1186\/1741-7015-11-127"},{"key":"e_1_2_13_84_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0006353"},{"key":"e_1_2_13_85_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-244X-11-18"},{"key":"e_1_2_13_86_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.22159"},{"key":"e_1_2_13_87_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.2482"},{"key":"e_1_2_13_88_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.161.5.896"},{"key":"e_1_2_13_89_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.06.013"},{"key":"e_1_2_13_90_1","doi-asserted-by":"crossref","unstructured":"Dagnew T. M. Squarcina L. Rivolta M. W. Brambilla P. &Sassi R.(2017).Learning from enhanced contextual similarity in brain imaging data for classification of schizophrenia. Paper presented at the International Conference on Image Analysis and Processing.","DOI":"10.1007\/978-3-319-68560-1_24"},{"key":"e_1_2_13_91_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00063"},{"key":"e_1_2_13_92_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1088-467X(97)00008-5"},{"key":"e_1_2_13_93_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2005.08.009"},{"key":"e_1_2_13_94_1","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.62.11.1218"},{"key":"e_1_2_13_95_1","doi-asserted-by":"publisher","DOI":"10.1111\/acps.12964"},{"key":"e_1_2_13_96_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0206351"},{"key":"e_1_2_13_97_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.10.012"},{"key":"e_1_2_13_98_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-008-9028-1"},{"key":"e_1_2_13_99_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23215"},{"key":"e_1_2_13_100_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnpbp.2017.09.006"},{"key":"e_1_2_13_101_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2013.00670"},{"key":"e_1_2_13_102_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2379621"},{"key":"e_1_2_13_103_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00075"},{"key":"e_1_2_13_104_1","doi-asserted-by":"publisher","DOI":"10.3389\/fncir.2014.00064"},{"key":"e_1_2_13_105_1","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2013.78"},{"key":"e_1_2_13_106_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2014.12.005"},{"key":"e_1_2_13_107_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22956"},{"key":"e_1_2_13_108_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2017.00362"},{"key":"e_1_2_13_109_1","unstructured":"Dodonova Y. Belyaev M. Tkachev A. Petrov D. &Zhukov L.(2016).Kernel classification of connectomes based on earth mover's distance between graph spectra.arXiv preprint arXiv:1611.08812."},{"key":"e_1_2_13_110_1","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/380531"},{"key":"e_1_2_13_111_1","doi-asserted-by":"publisher","DOI":"10.1038\/nm.4246"},{"key":"e_1_2_13_112_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2016.04.004"},{"key":"e_1_2_13_113_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2012.00145"},{"key":"e_1_2_13_114_1","unstructured":"Du Y. Fu Z. Lin D. Salman M. Rahaman M. Abrol A. \u2026Calhoun V.(2019). A unified ICA framework for identifying neuromarkers in resting fMRI functional connectivity among multiple different brain disorders.Proceedings of the ISMRM."},{"key":"e_1_2_13_115_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.07.054"},{"key":"e_1_2_13_116_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2015.11.021"},{"key":"e_1_2_13_117_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sby008"},{"key":"e_1_2_13_118_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.5413-09.2010"},{"key":"e_1_2_13_119_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.08.024"},{"key":"e_1_2_13_120_1","first-page":"111","article-title":"Leave\u2010one\u2010out error and stability of learning algorithms with applications","volume":"190","author":"Elisseeff A.","year":"2003","journal-title":"NATO Science Series Sub Series Iii Computer and Systems Sciences"},{"key":"e_1_2_13_121_1","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aag2882"},{"key":"e_1_2_13_122_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2017.3610"},{"key":"e_1_2_13_123_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2019.19050521"},{"key":"e_1_2_13_124_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00080"},{"key":"e_1_2_13_125_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1115365109"},{"key":"e_1_2_13_126_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2007.03.015"},{"key":"e_1_2_13_127_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.03.051"},{"key":"e_1_2_13_128_1","doi-asserted-by":"crossref","unstructured":"Fan Y. Shen D. &Davatzikos C.(2005).Classification of structural images via high\u2010dimensional image warping robust feature extraction and SVM. Paper presented at the International Conference on Medical Image Computing and Computer\u2010Assisted Intervention.","DOI":"10.1007\/11566465_1"},{"key":"e_1_2_13_129_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2006.886812"},{"key":"e_1_2_13_130_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0045972"},{"key":"e_1_2_13_131_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0062867"},{"key":"e_1_2_13_132_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-007-9003-9"},{"key":"e_1_2_13_133_1","doi-asserted-by":"publisher","DOI":"10.1214\/12-AOAS562"},{"key":"e_1_2_13_134_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdevneu.2015.07.007"},{"key":"e_1_2_13_135_1","volume-title":"Feature selection using lasso","author":"Fonti V.","year":"2017"},{"key":"e_1_2_13_136_1","unstructured":"Ford J. Shen L. Makedon F. Flashman L. A. &Saykin A. J.(2002).A combined structural\u2010functional classification of schizophrenia using hippocampal volume plus fMRI activation. Paper presented at the Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society Engineering in Medicine and Biology."},{"key":"e_1_2_13_137_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbn140"},{"key":"e_1_2_13_138_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.11.024"},{"key":"e_1_2_13_139_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.08.047"},{"key":"e_1_2_13_140_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2201"},{"key":"e_1_2_13_141_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.08.066"},{"key":"e_1_2_13_142_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.01.005"},{"key":"e_1_2_13_143_1","first-page":"6.41","article-title":"Diagnostic classification of autism using resting\u2010state fMRI data and conditional random forest","volume":"12","author":"Fredo A. J.","year":"2018","journal-title":"Age (years)"},{"key":"e_1_2_13_144_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbr.2013.11.003"},{"key":"e_1_2_13_145_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.25.112701.142846"},{"key":"e_1_2_13_146_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.460020402"},{"key":"e_1_2_13_147_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2007.08.020"},{"key":"e_1_2_13_148_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12888-015-0685-5"},{"key":"e_1_2_13_149_1","doi-asserted-by":"publisher","DOI":"10.1111\/cns.13048"},{"key":"e_1_2_13_150_1","doi-asserted-by":"crossref","unstructured":"Gao S. Osuch E. A. Wammes M. Th\u00e9berge J. Jiang T.\u2010Z. Calhoun V. D. &Sui J.(2017).Discriminating bipolar disorder from major depression based on kernel SVM using functional independent components. Paper presented at the 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).","DOI":"10.1109\/MLSP.2017.8168110"},{"key":"e_1_2_13_151_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2018.00055"},{"key":"e_1_2_13_152_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2018.00038"},{"key":"e_1_2_13_153_1","doi-asserted-by":"crossref","unstructured":"Gheiratmand M. Rish I. Cecchi G. A. Brown M. R. Greiner R. Polosecki P. I. \u2026Dursun S. M.(2017). Learning stable and predictive network\u2010based patterns of schizophrenia and its clinical symptoms.npj Schizophrenia 3(1) 22.","DOI":"10.1038\/s41537-017-0022-8"},{"key":"e_1_2_13_154_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0166934"},{"key":"e_1_2_13_155_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-013-9184-3"},{"key":"e_1_2_13_156_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291713000561"},{"key":"e_1_2_13_157_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.11.079"},{"key":"e_1_2_13_158_1","doi-asserted-by":"publisher","DOI":"10.1111\/jon.12280"},{"key":"e_1_2_13_159_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2014.09.009"},{"key":"e_1_2_13_160_1","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2012.84"},{"key":"e_1_2_13_161_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2012.00053"},{"key":"e_1_2_13_162_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0135058100"},{"key":"e_1_2_13_163_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22380"},{"key":"e_1_2_13_164_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00406-012-0329-4"},{"key":"e_1_2_13_165_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22551"},{"key":"e_1_2_13_166_1","doi-asserted-by":"publisher","DOI":"10.1111\/acps.12848"},{"key":"e_1_2_13_167_1","doi-asserted-by":"publisher","DOI":"10.4103\/1673-5374.125344"},{"key":"e_1_2_13_168_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22162"},{"key":"e_1_2_13_169_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291716000994"},{"key":"e_1_2_13_170_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euroneuro.2014.01.004"},{"key":"e_1_2_13_171_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2017.00179"},{"key":"e_1_2_13_172_1","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"Guyon I.","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_13_173_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.01.056"},{"key":"e_1_2_13_174_1","doi-asserted-by":"publisher","DOI":"10.1162\/0899766053723023"},{"key":"e_1_2_13_175_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2013.05.001"},{"key":"e_1_2_13_176_1","doi-asserted-by":"publisher","DOI":"10.1001\/archgenpsychiatry.2010.178"},{"key":"e_1_2_13_177_1","first-page":"181","volume-title":"Computer Science '98 Proceedings of the 21st Australasian Computer Science Conference ACSC'98, Perth, 4\u20106 February, 1998","author":"Hall M. A.","year":"1998"},{"key":"e_1_2_13_178_1","doi-asserted-by":"crossref","unstructured":"Han S. Huang W. Zhang Y. Zhao J. &Chen H.(2017).Recognition of early\u2010onset schizophrenia using deep\u2010learning method. Paper presented at the Applied Informatics.","DOI":"10.1186\/s40535-017-0044-3"},{"key":"e_1_2_13_179_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22386"},{"key":"e_1_2_13_180_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaac.2013.12.024"},{"key":"e_1_2_13_181_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-017-1451-x"},{"key":"e_1_2_13_182_1","doi-asserted-by":"publisher","DOI":"10.1037\/0894-4105.12.3.426"},{"key":"e_1_2_13_183_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2017.08.017"},{"issue":"3","key":"e_1_2_13_184_1","doi-asserted-by":"crossref","first-page":"e00633","DOI":"10.1002\/brb3.633","article-title":"Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study","volume":"7","author":"Hilbert K.","year":"2017","journal-title":"Brain and Behavior: A Cognitive Neuroscience Perspective"},{"key":"e_1_2_13_185_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.03.048"},{"key":"e_1_2_13_186_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2012.2206047"},{"key":"e_1_2_13_187_1","unstructured":"Hosseini\u2010Asl E. Gimel'farb G. &El\u2010Baz A.(2016). Alzheimer's disease diagnostics by a deeply supervised adaptable 3D convolutional network.arXiv preprint arXiv:1607.00556."},{"key":"e_1_2_13_188_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2019.2904301"},{"key":"e_1_2_13_189_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euroneuro.2015.12.014"},{"key":"e_1_2_13_190_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2018.04.026"},{"key":"e_1_2_13_191_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00787-015-0678-4"},{"key":"e_1_2_13_192_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2012.08.002"},{"key":"e_1_2_13_193_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2014.08.011"},{"key":"e_1_2_13_194_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.05.023"},{"key":"e_1_2_13_195_1","doi-asserted-by":"crossref","unstructured":"Ingalhalikar M. Smith A. R. Bloy L. Gur R. Roberts T. P. &Verma R.(2012).Identifying sub\u2010populations via unsupervised cluster analysis on multi\u2010edge similarity graphs. Paper presented at the International Conference on Medical Image Computing and Computer\u2010Assisted Intervention.","DOI":"10.1007\/978-3-642-33418-4_32"},{"key":"e_1_2_13_196_1","volume-title":"Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders","author":"Insel T.","year":"2010"},{"key":"e_1_2_13_197_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2014.14020138"},{"key":"e_1_2_13_198_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2013.00095"},{"key":"e_1_2_13_199_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.mp.4001857"},{"key":"e_1_2_13_200_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.11.001"},{"key":"e_1_2_13_201_1","doi-asserted-by":"publisher","DOI":"10.1089\/brain.2017.0496"},{"key":"e_1_2_13_202_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.574797"},{"key":"e_1_2_13_203_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.04.003"},{"key":"e_1_2_13_204_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00392"},{"key":"e_1_2_13_205_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2015.03.004"},{"key":"e_1_2_13_206_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.12.047"},{"key":"e_1_2_13_207_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2013.2284195"},{"key":"e_1_2_13_208_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2015.2440298"},{"key":"e_1_2_13_209_1","doi-asserted-by":"publisher","DOI":"10.18632\/oncotarget.19860"},{"key":"e_1_2_13_210_1","doi-asserted-by":"publisher","DOI":"10.1093\/biostatistics\/kxj037"},{"key":"e_1_2_13_211_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22542"},{"key":"e_1_2_13_212_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0132958"},{"key":"e_1_2_13_213_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awv177"},{"key":"e_1_2_13_214_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0113879"},{"key":"e_1_2_13_215_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2015.22"},{"key":"e_1_2_13_216_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-010-9094-6"},{"key":"e_1_2_13_217_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2010.09.016"},{"key":"e_1_2_13_218_1","first-page":"471169","article-title":"Early brain imaging can predict autism: Application of machine learning to a clinical imaging archive","volume":"2018","author":"Katuwal G. J.","year":"2018","journal-title":"BioRxiv"},{"key":"e_1_2_13_219_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbv060"},{"key":"e_1_2_13_220_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.08.018"},{"key":"e_1_2_13_221_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2005.04.034"},{"key":"e_1_2_13_222_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-010-9077-7"},{"key":"e_1_2_13_223_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.05.018"},{"key":"e_1_2_13_224_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.11.002"},{"key":"e_1_2_13_225_1","doi-asserted-by":"publisher","DOI":"10.1212\/01.wnl.0000341768.28646.b6"},{"key":"e_1_2_13_226_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awn091"},{"key":"e_1_2_13_227_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0119089"},{"key":"e_1_2_13_228_1","unstructured":"Kohavi R.(1995).A study of cross\u2010validation and bootstrap for accuracy estimation and model selection. Paper presented at the IJCAI."},{"key":"e_1_2_13_229_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24202"},{"key":"e_1_2_13_230_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awv111"},{"key":"e_1_2_13_231_1","doi-asserted-by":"publisher","DOI":"10.1001\/archgenpsychiatry.2009.62"},{"key":"e_1_2_13_232_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-vision-082114-035447"},{"key":"e_1_2_13_233_1","doi-asserted-by":"publisher","DOI":"10.1002\/wps.20566"},{"key":"e_1_2_13_234_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.12.052"},{"key":"e_1_2_13_235_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-35488-8_6"},{"key":"e_1_2_13_236_1","doi-asserted-by":"publisher","DOI":"10.4088\/JCP.09m05398blu"},{"key":"e_1_2_13_237_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2018.02.007"},{"key":"e_1_2_13_238_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.11.004"},{"key":"e_1_2_13_239_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22357"},{"key":"e_1_2_13_240_1","doi-asserted-by":"crossref","unstructured":"Li F. Tran L. Thung K.\u2010H. Ji S. Shen D. &Li J.(2014).Robust deep learning for improved classification of AD\/MCI patients. Paper presented at the International Workshop on Machine Learning in Medical Imaging.","DOI":"10.1007\/978-3-319-10581-9_30"},{"key":"e_1_2_13_241_1","doi-asserted-by":"publisher","DOI":"10.1111\/acps.12752"},{"key":"e_1_2_13_242_1","unstructured":"Li Y. Lian Z. Li M. Liu Z. Xiao L. &Wei Z.(2016).ELM\u2010based classification of ADHD patients using a novel local feature extraction method. Paper presented at the 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)."},{"key":"e_1_2_13_243_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sby091"},{"key":"e_1_2_13_244_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2015.02.008"},{"key":"e_1_2_13_245_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0063660"},{"key":"e_1_2_13_246_1","unstructured":"Lin D. Du Y. Fu Z. Salman M. Rahaman M. Abrol A. \u2026Calhoun V.(2018).Cross\u2010cohort study of neurological resting fMRI biomarkers for schizophrenia on resting fMRI. Proceedings of the HBM."},{"key":"e_1_2_13_247_1","unstructured":"Lin D. Du Y. Fu Z. Salman M. Rahaman M. Abrol A. \u2026Calhoun V.(2019).Cross\u2010cohort study of resting fMRI biomarkers for schizophrenia. Proceedings of the HBM."},{"key":"e_1_2_13_248_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-013-0641-4"},{"key":"e_1_2_13_249_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0040968"},{"key":"e_1_2_13_250_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2014.00029"},{"key":"e_1_2_13_251_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNB.2017.2751074"},{"key":"e_1_2_13_252_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20508"},{"key":"e_1_2_13_253_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-5470-7"},{"key":"e_1_2_13_254_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40708-015-0019-x"},{"key":"e_1_2_13_255_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2014.2372011"},{"key":"e_1_2_13_256_1","doi-asserted-by":"publisher","DOI":"10.1093\/ijnp\/pyx095"},{"key":"e_1_2_13_257_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2017.04.028"},{"key":"e_1_2_13_258_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0041282"},{"key":"e_1_2_13_259_1","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000003973"},{"key":"e_1_2_13_260_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00702-014-1272-5"},{"key":"e_1_2_13_261_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0053148"},{"key":"e_1_2_13_262_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-013-9264-x"},{"key":"e_1_2_13_263_1","doi-asserted-by":"publisher","DOI":"10.1097\/WNR.0b013e328310425e"},{"key":"e_1_2_13_264_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2015.12.023"},{"key":"e_1_2_13_265_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhx319"},{"key":"e_1_2_13_266_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.07.020"},{"key":"e_1_2_13_267_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1"},{"key":"e_1_2_13_268_1","doi-asserted-by":"crossref","unstructured":"Miao B. &Zhang Y. (2017).A feature selection method for classification of ADHD. Paper presented at the 2017 4th International Conference on Information Cybernetics and Computational Social Systems (ICCSS).","DOI":"10.1109\/ICCSS.2017.8091376"},{"key":"e_1_2_13_269_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12888-018-1678-y"},{"key":"e_1_2_13_270_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291716000878"},{"key":"e_1_2_13_271_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-04976-1"},{"key":"e_1_2_13_272_1","doi-asserted-by":"publisher","DOI":"10.12688\/f1000research.12353.1"},{"key":"e_1_2_13_273_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000035475.85309.1b"},{"key":"e_1_2_13_274_1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.42"},{"key":"e_1_2_13_275_1","doi-asserted-by":"publisher","DOI":"10.1038\/jcbfm.1991.47"},{"key":"e_1_2_13_276_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2018.00071"},{"key":"e_1_2_13_277_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.10.002"},{"key":"e_1_2_13_278_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2005.06.070"},{"key":"e_1_2_13_279_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.06.042"},{"key":"e_1_2_13_280_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0029482"},{"key":"e_1_2_13_281_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2014.3176"},{"key":"e_1_2_13_282_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0050064"},{"key":"e_1_2_13_283_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/aws084"},{"key":"e_1_2_13_284_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-013-9204-3"},{"key":"e_1_2_13_285_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.schbul.a007087"},{"key":"e_1_2_13_286_1","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2015.76"},{"key":"e_1_2_13_287_1","doi-asserted-by":"crossref","unstructured":"Nie D. Zhang H. Adeli E. Liu L. &Shen D.(2016).3D deep learning for multi\u2010modal imaging\u2010guided survival time prediction of brain tumor patients. Paper presented at the International conference on medical image computing and computer\u2010assisted intervention.","DOI":"10.1007\/978-3-319-46723-8_25"},{"key":"e_1_2_13_288_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2013.00599"},{"key":"e_1_2_13_289_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.03.079"},{"key":"e_1_2_13_290_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.05.023"},{"key":"e_1_2_13_291_1","first-page":"1","article-title":"Using structural MRI to identify bipolar disorders\u201313 site machine learning study in 3020 individuals from the ENIGMA bipolar disorders working group","author":"Nunes A.","year":"2018","journal-title":"Molecular Psychiatry"},{"key":"e_1_2_13_292_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2012.01.004"},{"issue":"11","key":"e_1_2_13_293_1","first-page":"8","article-title":"Sample size and subject to item ratio in principal components analysis","volume":"9","author":"Osborne J. W.","year":"2004","journal-title":"Practical Assessment, Research & Evaluation"},{"key":"e_1_2_13_294_1","doi-asserted-by":"publisher","DOI":"10.1111\/acps.12945"},{"key":"e_1_2_13_295_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2013.06.010"},{"key":"e_1_2_13_296_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1440-1819.2012.02397.x"},{"key":"e_1_2_13_297_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_2_13_298_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2016.00009"},{"key":"e_1_2_13_299_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2006.05.007"},{"key":"e_1_2_13_300_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00425"},{"key":"e_1_2_13_301_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10548-015-0463-1"},{"key":"e_1_2_13_302_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2014.01.006"},{"key":"e_1_2_13_303_1","doi-asserted-by":"publisher","DOI":"10.1002\/gps.4262"},{"key":"e_1_2_13_304_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2015.11.003"},{"key":"e_1_2_13_305_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.psc.2016.01.001"},{"key":"e_1_2_13_306_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0079476"},{"key":"e_1_2_13_307_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.11.007"},{"key":"e_1_2_13_308_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2016.07.005"},{"key":"e_1_2_13_309_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2014.00189"},{"key":"e_1_2_13_310_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00787-014-0593-0"},{"key":"e_1_2_13_311_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.07.047"},{"key":"e_1_2_13_312_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2014.00229"},{"key":"e_1_2_13_313_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00365"},{"key":"e_1_2_13_314_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2014.12.013"},{"key":"e_1_2_13_315_1","doi-asserted-by":"crossref","unstructured":"Pohl K. M. &Sabuncu M. R.(2009).A unified framework for MR based disease classification. Paper presented at the International Conference on Information Processing in Medical Imaging.","DOI":"10.1007\/978-3-642-02498-6_25"},{"key":"e_1_2_13_316_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2014.08.001"},{"key":"e_1_2_13_317_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2725306"},{"key":"e_1_2_13_318_1","first-page":"595017","article-title":"Parallel group ICA+ ICA: Joint estimation of linked functional network variability and structural covariation with application to schizophrenia","volume":"2019","author":"Qi S.","year":"2019","journal-title":"BioRxiv"},{"key":"e_1_2_13_319_1","doi-asserted-by":"crossref","unstructured":"Qureshi M. N. I. Jo H. J. &Lee B.(2017).ADHD subgroup discrimination with global connectivity features using hierarchical extreme learning machine: Resting\u2010state FMRI study. Paper presented at the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).","DOI":"10.1109\/ISBI.2017.7950576"},{"key":"e_1_2_13_320_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2017.00059"},{"key":"e_1_2_13_321_1","first-page":"157","article-title":"Multi\u2010modal, multi\u2010measure, and multi\u2010class discrimination of ADHD with hierarchical feature extraction and extreme learning machine using structural and functional brain MRI","volume":"11","author":"Qureshi M. N. I.","year":"2017","journal-title":"Frontiers in Human Neuroscience"},{"key":"e_1_2_13_322_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2014.05.014"},{"key":"e_1_2_13_323_1","doi-asserted-by":"crossref","unstructured":"Rahaman M. Damaraju E. &Calhoun V.(2019).A novel method for triclustering dynamic functional connectivity (dFNC) data identifies significant schizophrenia effects across multiple states in distinct subgroups of individuals. Paper presented at the Proc HBM.","DOI":"10.1101\/2020.08.06.239152"},{"key":"e_1_2_13_324_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2019.2908815"},{"key":"e_1_2_13_325_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2016.07.012"},{"key":"e_1_2_13_326_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.04.051"},{"key":"e_1_2_13_327_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24064"},{"key":"e_1_2_13_328_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.10.004"},{"key":"e_1_2_13_329_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00897"},{"key":"e_1_2_13_330_1","doi-asserted-by":"crossref","unstructured":"Rathi Y. Malcolm J. Michailovich O. Goldstein J. Seidman L. McCarley R. W. \u2026Shenton M. E.(2010).Biomarkers for identifying first\u2010episode schizophrenia patients using diffusion weighted imaging. Paper presented at the International Conference on Medical Image Computing and Computer\u2010Assisted Intervention.","DOI":"10.1007\/978-3-642-15705-9_80"},{"key":"e_1_2_13_331_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2014.1100"},{"key":"e_1_2_13_332_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-39940-9_565"},{"key":"e_1_2_13_333_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00306"},{"issue":"4","key":"e_1_2_13_334_1","first-page":"231","article-title":"Neuroimaging\u2010based methods for autism identification: A possible translational application?","volume":"29","author":"Retico A.","year":"2014","journal-title":"Functional Neurology"},{"key":"e_1_2_13_335_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2017.10.002"},{"key":"e_1_2_13_336_1","doi-asserted-by":"publisher","DOI":"10.1111\/bdi.12446"},{"key":"e_1_2_13_337_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2281398"},{"key":"e_1_2_13_338_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.11.021"},{"key":"e_1_2_13_339_1","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbx137"},{"key":"e_1_2_13_340_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2017.11.043"},{"key":"e_1_2_13_341_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2015.06.002"},{"key":"e_1_2_13_342_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2015.00021"},{"key":"e_1_2_13_343_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2017.02.004"},{"key":"e_1_2_13_344_1","doi-asserted-by":"publisher","DOI":"10.1523\/ENEURO.0384-19.2019"},{"key":"e_1_2_13_345_1","doi-asserted-by":"crossref","unstructured":"Saha D. Abrol A. Damaraju E. Rashid B. Plis S. &Calhoun V.(2019).Classification as a criterion to select model order for dynamic functional connectivity states in rest\u2010fMRI data. Paper presented at the 2019 IEEE 12th International Symposium on Biomedical Imaging (ISBI).","DOI":"10.1109\/ISBI.2019.8759146"},{"key":"e_1_2_13_346_1","unstructured":"Saha D. Damaraju E. Rashid B. Abrol A. Plis S. &Calhoun V.(2019).A combinatorial approach to improve the classification accuracy in resting state fMRI data. Proceedings of the HBM."},{"key":"e_1_2_13_347_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10334-010-0197-8"},{"key":"e_1_2_13_348_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.11.046"},{"key":"e_1_2_13_349_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0175683"},{"key":"e_1_2_13_350_1","doi-asserted-by":"publisher","DOI":"10.1192\/bjpo.bp.115.002493"},{"key":"e_1_2_13_351_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpsychires.2012.11.017"},{"key":"e_1_2_13_352_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00068"},{"key":"e_1_2_13_353_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2015.07.001"},{"key":"e_1_2_13_354_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2014.11.018"},{"key":"e_1_2_13_355_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"e_1_2_13_356_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2016.00050"},{"key":"e_1_2_13_357_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.08.053"},{"key":"e_1_2_13_358_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2017.03.003"},{"key":"e_1_2_13_359_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-013-9178-1"},{"key":"e_1_2_13_360_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euroneuro.2013.09.010"},{"key":"e_1_2_13_361_1","doi-asserted-by":"publisher","DOI":"10.3389\/fncom.2014.00060"},{"key":"e_1_2_13_362_1","doi-asserted-by":"publisher","DOI":"10.1093\/arclin\/11.6.521"},{"key":"e_1_2_13_363_1","doi-asserted-by":"crossref","unstructured":"Sen B. Bernstein G. A. Xu T. Mueller B. A. Schreiner M. W. Cullen K. R. &Parhi K. K.(2016).Classification of obsessive\u2010compulsive disorder from resting\u2010state fMRI. Paper presented at the 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).","DOI":"10.1109\/EMBC.2016.7591508"},{"key":"e_1_2_13_364_1","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/706157"},{"key":"e_1_2_13_365_1","doi-asserted-by":"crossref","unstructured":"Shao J. Yu Z. Li P. Han W. Sorg C. &Yang Q.(2017).Exploring common and distinct structural connectivity patterns between schizophrenia and major depression via cluster\u2010driven nonnegative matrix factorization. Paper presented at the 2017 IEEE International Conference on Data Mining (ICDM).","DOI":"10.1109\/ICDM.2017.142"},{"key":"e_1_2_13_366_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.07.011"},{"key":"e_1_2_13_367_1","doi-asserted-by":"publisher","DOI":"10.1097\/WNR.0000000000000267"},{"key":"e_1_2_13_368_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.11.011"},{"key":"e_1_2_13_369_1","doi-asserted-by":"crossref","unstructured":"Shenas S. K. Halici U. &Cicek M.(2013).Detection of obsessive compulsive disorder using resting\u2010state functional connectivity data. Paper presented at the 2013 6th International Conference on Biomedical Engineering and Informatics.","DOI":"10.1109\/BMEI.2013.6746921"},{"key":"e_1_2_13_370_1","doi-asserted-by":"crossref","unstructured":"Shenas S. K. Halici U. &\u00c7i\u00e7ek M.(2014).A comparative analysis of functional connectivity data in resting and task\u2010related conditions of the brain for disease signature of OCD. Paper presented at the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.","DOI":"10.1109\/EMBC.2014.6943756"},{"key":"e_1_2_13_371_1","unstructured":"Shi F. Liu Y. Jiang T. Zhou Y. Zhu W. Jiang J. \u2026Liu Z.(2007).Regional homogeneity and anatomical parcellation for fMRI image classification: Application to schizophrenia and normal controls. Paper presented at the International Conference on Medical Image Computing and Computer\u2010Assisted Intervention."},{"key":"e_1_2_13_372_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0123524"},{"key":"e_1_2_13_373_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2012.00074"},{"key":"e_1_2_13_374_1","doi-asserted-by":"crossref","unstructured":"Silva R. F. Castro E. Gupta C. N. Cetin M. Arbabshirani M. Potluru V. K. \u2026Calhoun V. D.(2014).The tenth annual MLSP competition: Schizophrenia classification challenge. Paper presented at the 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).","DOI":"10.1109\/MLSP.2014.6958889"},{"key":"e_1_2_13_375_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.01.011"},{"key":"e_1_2_13_376_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2018.00070"},{"key":"e_1_2_13_377_1","unstructured":"Springenberg J. T. Dosovitskiy A. Brox T. &Riedmiller M.(2014). Striving for simplicity: The all convolutional net.arXiv preprint arXiv:1412.6806."},{"key":"e_1_2_13_378_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2016.15121587"},{"key":"e_1_2_13_379_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2017.07.003"},{"key":"e_1_2_13_380_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.09.066"},{"key":"e_1_2_13_381_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2013.00702"},{"key":"e_1_2_13_382_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.01.026"},{"key":"e_1_2_13_383_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2011.10.031"},{"key":"e_1_2_13_384_1","unstructured":"Sui J. Castro E. He H. Bridwell D. Du Y. Pearlson G. D. \u2026Calhoun V. D.(2014).Combination of FMRI\u2010SMRI\u2010EEG data improves discrimination of schizophrenia patients by ensemble feature selection. Paper presented at the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society."},{"key":"e_1_2_13_385_1","unstructured":"Sui J. He H. Liu J. Yu Q. Adali T. Pearlson G. D. &Calhoun V. D.(2012).Three\u2010way FMRI\u2010DTI\u2010methylation data fusion based on mCCA+ jICA and its application to schizophrenia. Paper presented at the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society."},{"key":"e_1_2_13_386_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.10.051"},{"key":"e_1_2_13_387_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2013.00235"},{"key":"e_1_2_13_388_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2015.02.017"},{"key":"e_1_2_13_389_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-05432-w"},{"key":"e_1_2_13_390_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-013-0687-3"},{"key":"e_1_2_13_391_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2009.07.019"},{"key":"e_1_2_13_392_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00702-016-1673-8"},{"key":"e_1_2_13_393_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A3713"},{"key":"e_1_2_13_394_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-07792-7"},{"key":"e_1_2_13_395_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0021047"},{"key":"e_1_2_13_396_1","doi-asserted-by":"publisher","DOI":"10.1186\/1475-925X-11-50"},{"key":"e_1_2_13_397_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2451-0"},{"key":"e_1_2_13_398_1","unstructured":"Tejwani R. Liska A. You H. Reinen J. &Das P.(2017). Autism classification using brain functional connectivity dynamics and machine learning.arXiv preprint arXiv:1712.08041."},{"key":"e_1_2_13_399_1","first-page":"62","article-title":"The ADHD\u2010200 consortium: A model to advance the translational potential of neuroimaging in clinical neuroscience","volume":"6","author":"The ADHD\u2010200 Consortium","year":"2012","journal-title":"Frontiers in Systems Neuroscience"},{"key":"e_1_2_13_400_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2013.00187"},{"key":"e_1_2_13_401_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2017.06.061"},{"key":"e_1_2_13_402_1","volume-title":"The elements of statistical learning: Data mining, inference, and prediction","author":"Trevor H.","year":"2009"},{"key":"e_1_2_13_403_1","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2017.164"},{"key":"e_1_2_13_404_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2011.07.014"},{"key":"e_1_2_13_405_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2013.104"},{"key":"e_1_2_13_406_1","unstructured":"Ulloa A. Plis S. &Calhoun V.(2018). Improving Classification Rate of Schizophrenia Using a Multimodal Multi\u2010Layer Perceptron Model with Structural and Functional MR.arXiv preprint arXiv:1804.04591."},{"key":"e_1_2_13_407_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2012.01.003"},{"key":"e_1_2_13_408_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291714001792"},{"key":"e_1_2_13_409_1","doi-asserted-by":"publisher","DOI":"10.1186\/1741-7015-10-156"},{"key":"e_1_2_13_410_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.10.038"},{"key":"e_1_2_13_411_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2012.04.021"},{"key":"e_1_2_13_412_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.03.038"},{"key":"e_1_2_13_413_1","doi-asserted-by":"publisher","DOI":"10.1038\/npp.2017.280"},{"key":"e_1_2_13_414_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2017.01.002"},{"key":"e_1_2_13_415_1","doi-asserted-by":"crossref","unstructured":"Vy\u0161kovsk\u00fd R. Schwarz D. Janou\u0161ov\u00e1 E. &Ka\u0161p\u00e1rek T.(2016).Random subspace ensemble artificial neural networks for first\u2010episode Schizophrenia classification. Paper presented at the 2016 federated conference on computer science and information systems (FedCSIS).","DOI":"10.15439\/2016F333"},{"key":"e_1_2_13_416_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0045502"},{"key":"e_1_2_13_417_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-015-9360-1"},{"key":"e_1_2_13_418_1","unstructured":"Wang X. Hutchinson R. &Mitchell T. M.(2004).Training fMRI classifiers to detect cognitive states across multiple human subjects. Paper presented at the Advances in neural information processing systems."},{"key":"e_1_2_13_419_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2013.04.009"},{"key":"e_1_2_13_420_1","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/3609821"},{"key":"e_1_2_13_421_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-30308-w"},{"key":"e_1_2_13_422_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.12.092"},{"key":"e_1_2_13_423_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.03.067"},{"key":"e_1_2_13_424_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22411"},{"key":"e_1_2_13_425_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pscychresns.2013.09.008"},{"key":"e_1_2_13_426_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.58337"},{"key":"e_1_2_13_427_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.01.064"},{"key":"e_1_2_13_428_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23115"},{"key":"e_1_2_13_429_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2017.11.038"},{"key":"e_1_2_13_430_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2015.08.001"},{"key":"e_1_2_13_431_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2016.06.020"},{"key":"e_1_2_13_432_1","doi-asserted-by":"crossref","unstructured":"Wong E. Anderson J. S. Zielinski B. A. &Fletcher P. T.(2018).Riemannian regression and classification models of brain networks applied to autism. Paper presented at the International Workshop on Connectomics in Neuroimaging.","DOI":"10.1007\/978-3-030-00755-3_9"},{"key":"e_1_2_13_433_1","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4478"},{"key":"e_1_2_13_434_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40708-016-0047-1"},{"key":"e_1_2_13_435_1","doi-asserted-by":"publisher","DOI":"10.1002\/aur.1711"},{"key":"e_1_2_13_436_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(16)31963-8"},{"key":"e_1_2_13_437_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2010.00192"},{"key":"e_1_2_13_438_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24282"},{"key":"e_1_2_13_439_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2015.05.034"},{"key":"e_1_2_13_440_1","doi-asserted-by":"crossref","unstructured":"Yao D. Guo X. Zhao Q. Liu L. Cao Q. Wang Y. \u2026Sui J.(2018).Discriminating ADHD from healthy controls using a novel feature selection method based on relative importance and ensemble learning. Paper presented at the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).","DOI":"10.1109\/EMBC.2018.8513155"},{"key":"e_1_2_13_441_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2012.01.001"},{"key":"e_1_2_13_442_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2008.07.025"},{"key":"e_1_2_13_443_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0179638"},{"key":"e_1_2_13_444_1","unstructured":"Yosinski J. Clune J. Nguyen A. Fuchs T. &Lipson H.(2015). Understanding neural networks through deep visualization.arXiv preprint arXiv:1506.06579."},{"key":"e_1_2_13_445_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0068250"},{"key":"e_1_2_13_446_1","doi-asserted-by":"publisher","DOI":"10.1186\/1475-925X-12-10"},{"key":"e_1_2_13_447_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnpbp.2015.06.009"},{"key":"e_1_2_13_448_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2005.06.014"},{"key":"e_1_2_13_449_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.03.047"},{"key":"e_1_2_13_450_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnpbp.2012.12.005"},{"key":"e_1_2_13_451_1","doi-asserted-by":"crossref","unstructured":"Zeiler M. D. &Fergus R.(2014).Visualizing and understanding convolutional networks. Paper presented at the European conference on computer vision.","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"e_1_2_13_452_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22278"},{"key":"e_1_2_13_453_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/aws059"},{"key":"e_1_2_13_454_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.10.029"},{"key":"e_1_2_13_455_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.39"},{"key":"e_1_2_13_456_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.04.063"},{"key":"e_1_2_13_457_1","doi-asserted-by":"crossref","unstructured":"Zhang Y. Tang Y. Chen Y. Zhou L. &Wang C.(2018).ADHD classification by feature space separation with sparse representation. Paper presented at the 2018 IEEE 23rd international conference on digital signal processing (DSP).","DOI":"10.1109\/ICDSP.2018.8631658"},{"key":"e_1_2_13_458_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2018.00184"},{"key":"e_1_2_13_459_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2017.04.040"},{"key":"e_1_2_13_460_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0090405"},{"key":"e_1_2_13_461_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.11.029"},{"key":"e_1_2_13_462_1","doi-asserted-by":"crossref","unstructured":"Zhu D. Shen D. Jiang X. &Liu T.(2014).Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. Paper presented at the 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).","DOI":"10.1109\/ISBI.2014.6867874"},{"key":"e_1_2_13_463_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-018-0464-x"},{"key":"e_1_2_13_464_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2018.04.007"},{"key":"e_1_2_13_465_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00503.x"}],"container-title":["Human Brain Mapping"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fhbm.25013","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hbm.25013","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/hbm.25013","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/hbm.25013","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T22:46:16Z","timestamp":1693953976000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/hbm.25013"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,6]]},"references-count":464,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,8,15]]}},"alternative-id":["10.1002\/hbm.25013"],"URL":"https:\/\/doi.org\/10.1002\/hbm.25013","archive":["Portico"],"relation":{},"ISSN":["1065-9471","1097-0193"],"issn-type":[{"value":"1065-9471","type":"print"},{"value":"1097-0193","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,6]]},"assertion":[{"value":"2019-11-21","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-04-06","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-05-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}