Sergey Plis

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Vince D. CalhounDirector-Translational Research in Neuroimaging and Data Science (TReNDS;GSU/GAtech/Emory)Patvirtintas el. paštas gsu.edu
Eswar DamarajuChildren's Healthcare of AtlantaPatvirtintas el. paštas choa.org
Jessica TurnerThe Ohio State University, Wexner Medical CenterPatvirtintas el. paštas osumc.edu
Rogers F SilvaTReNDS Center (Translational Research in Neuroimaging and Data Science); GSU/GATech/EmoryPatvirtintas el. paštas gsu.edu
R Devon HjelmApple MLR, MilaPatvirtintas el. paštas apple.com
Zening FuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDSPatvirtintas el. paštas gsu.edu
Anand SarwateAssociate Professor, Rutgers UniversityPatvirtintas el. paštas rutgers.edu
Jing SuiProfessor, State Key Lab of Cognitive Neuroscience & Learning, BNUPatvirtintas el. paštas bnu.edu.cn
Tom EicheleHead of Clinical Neurophysiology, Haukeland university hospitalPatvirtintas el. paštas helse-bergen.no
Elena AllenRodin ScientificPatvirtintas el. paštas rodinscientific.com
Alex FedorovEmory UniversityPatvirtintas el. paštas emory.edu
Anees AbrolResearch Scientist II, GSU/GATech/Emory TReNDS CenterPatvirtintas el. paštas gsu.edu
Erik Barry ErhardtProfessor of Statistics, University of New MexicoPatvirtintas el. paštas stat.unm.edu
Vamsi Krishna PotluruResearcherPatvirtintas el. paštas jpmchase.com
Tulay AdaliDistinguished University Professor, University of Maryland, Baltimore CountyPatvirtintas el. paštas umbc.edu
Heather Terran Laneathenahealth, Inc.Patvirtintas el. paštas illation.net
sandeep pantaSoftware engineerPatvirtintas el. paštas gsu.edu
Mohammad Reza Arbabshirani, PhDAmazon Web ServicesPatvirtintas el. paštas amazon.com
Sung Chan JunAI Graduate School/School of EECS, Gwangju Institute of Science and TechnologyPatvirtintas el. paštas gist.ac.kr
David DanksProfessor of Data Science, Philosophy, & Policy; UC San DiegoPatvirtintas el. paštas ucsd.edu

Stebėti

Sergey Plis

TReNDS center: GSU, Emory, and GATech

Patvirtintas el. paštas gsu.edu

Machine learning in brain imaging and beyond


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Tracking whole-brain connectivity dynamics in the resting state EA Allen, E Damaraju, SM Plis, EB Erhardt, T Eichele, VD Calhoun Cerebral cortex 24 (3), 663-676, 2014	3065	2014
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls MR Arbabshirani, S Plis, J Sui, VD Calhoun Neuroimage 145, 137-165, 2017	968	2017
Deep learning for neuroimaging: a validation study SM Plis, DR Hjelm, R Salakhutdinov, EA Allen, HJ Bockholt, JD Long, ... Frontiers in neuroscience 8, 229, 2014	685	2014
Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data A Aliper, S Plis, A Artemov, A Ulloa, P Mamoshina, A Zhavoronkov Molecular pharmaceutics 13 (7), 2524-2530, 2016	659	2016
Analysis of multimodal neuroimaging data F Biessmann, S Plis, FC Meinecke, T Eichele, KR Muller IEEE reviews in biomedical engineering 4, 26-58, 2011	194	2011
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning A Abrol, Z Fu, M Salman, R Silva, Y Du, S Plis, V Calhoun Nature communications 12 (1), 353, 2021	189	2021
Restricted Boltzmann machines for neuroimaging: an application in identifying intrinsic networks RD Hjelm, VD Calhoun, R Salakhutdinov, EA Allen, T Adali, SM Plis NeuroImage 96, 245-260, 2014	183	2014
Deep residual learning for neuroimaging: an application to predict progression to Alzheimer’s disease A Abrol, M Bhattarai, A Fedorov, Y Du, S Plis, V Calhoun, ... Journal of neuroscience methods 339, 108701, 2020	173	2020
Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks H Jang, SM Plis, VD Calhoun, JH Lee NeuroImage 145, 314-328, 2017	141	2017
Impact of autocorrelation on functional connectivity MR Arbabshirani, E Damaraju, R Phlypo, S Plis, E Allen, S Ma, ... Neuroimage 102, 294-308, 2014	116	2014
Learning to run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ... The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018	107	2018
Group-level component analyses of EEG: validation and evaluation RJ Huster, SM Plis, VD Calhoun Frontiers in neuroscience 9, 254, 2015	103	2015
COINSTAC: a privacy enabled model and prototype for leveraging and processing decentralized brain imaging data SM Plis, AD Sarwate, D Wood, C Dieringer, D Landis, C Reed, SR Panta, ... Frontiers in neuroscience 10, 365, 2016	100	2016
Automated interpretation of clinical electroencephalograms using artificial intelligence J Tveit, H Aurlien, S Plis, VD Calhoun, WO Tatum, DL Schomer, V Arntsen, ... JAMA neurology 80 (8), 805-812, 2023	97	2023
Modular organization of functional network connectivity in healthy controls and patients with schizophrenia during the resting state Q Yu, SM Plis, EB Erhardt, EA Allen, J Sui, KA Kiehl, G Pearlson, ... Frontiers in systems neuroscience 5, 103, 2012	96	2012
Independent component analysis for brain fMRI does indeed select for maximal independence VD Calhoun, VK Potluru, R Phlypo, RF Silva, BA Pearlmutter, A Caprihan, ... PloS one 8 (8), e73309, 2013	95	2013
Quantitative EEG biomarkers for mild traumatic brain injury JD Lewine, S Plis, A Ulloa, C Williams, M Spitz, J Foley, K Paulson, ... Journal of Clinical Neurophysiology 36 (4), 298-305, 2019	92	2019
Disrupted correlation between low frequency power and connectivity strength of resting state brain networks in schizophrenia Q Yu, J Sui, J Liu, SM Plis, KA Kiehl, G Pearlson, VD Calhoun Schizophrenia research 143 (1), 165-171, 2013	87	2013
Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data SC Jun, JS George, J Paré-Blagoev, SM Plis, DM Ranken, DM Schmidt, ... NeuroImage 28 (1), 84-98, 2005	82	2005
Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation AD Sarwate, SM Plis, JA Turner, MR Arbabshirani, VD Calhoun Frontiers in neuroinformatics 8, 35, 2014	68	2014

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