{"id":"https://openalex.org/W2789481482","doi":"https://doi.org/10.1109/access.2018.2815770","title":"Whole Brain fMRI Pattern Analysis Based on Tensor Neural Network","display_name":"Whole Brain fMRI Pattern Analysis Based on Tensor Neural Network","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2789481482","doi":"https://doi.org/10.1109/access.2018.2815770","mag":"2789481482"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2815770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2815770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2815770","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037803260","display_name":"Xiaowen Xu","orcid":"https://orcid.org/0000-0001-7414-0354"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowen Xu","raw_affiliation_strings":["Shandong University, Jinan, Shandong, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, Shandong, CN","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694041","display_name":"Qiang Wu","orcid":"https://orcid.org/0000-0002-6362-5169"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Wu","raw_affiliation_strings":["Shandong University, Jinan, Shandong, CN"],"raw_orcid":"https://orcid.org/0000-0002-6362-5169","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, Shandong, CN","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045409266","display_name":"Shuo Wang","orcid":"https://orcid.org/0000-0003-2562-0225"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Wang","raw_affiliation_strings":["Shandong University, Jinan, Shandong, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, Shandong, CN","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102010401","display_name":"Ju Liu","orcid":"https://orcid.org/0000-0003-2622-9666"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ju Liu","raw_affiliation_strings":["Shandong University, Jinan, Shandong, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, Shandong, CN","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080244427","display_name":"Jiande Sun","orcid":"https://orcid.org/0000-0001-6157-2051"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiande Sun","raw_affiliation_strings":["Shandong Normal University, Jinan, Shandong, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Normal University, Jinan, Shandong, CN","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]},{"id":"https://openalex.org/I3019271933","display_name":"Nicolaus Copernicus University","ror":"https://ror.org/0102mm775","country_code":"PL","type":"education","lineage":["https://openalex.org/I3019271933"]}],"countries":["PL","RU"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["Nicolaus Copernicus University, Toru\u0144, Poland","Riken, Wako, Japan","Skolkovo Institute of Science and Technology, Moscow, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nicolaus Copernicus University, Toru\u0144, Poland","institution_ids":["https://openalex.org/I3019271933"]},{"raw_affiliation_string":"Riken, Wako, Japan","institution_ids":[]},{"raw_affiliation_string":"Skolkovo Institute of Science and Technology, Moscow, Russia","institution_ids":["https://openalex.org/I125989756"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2046,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.72792023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"6","issue":null,"first_page":"29297","last_page":"29305"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7770704627037048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.73861163854599},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6941334009170532},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6550225019454956},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6389003992080688},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.5797327160835266},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5774136781692505},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5551139712333679},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5393080711364746},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5184690356254578},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5064092874526978},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4998903274536133},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40304750204086304},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07710301876068115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770704627037048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.73861163854599},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6941334009170532},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6550225019454956},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6389003992080688},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.5797327160835266},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5774136781692505},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5551139712333679},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5393080711364746},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5184690356254578},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5064092874526978},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4998903274536133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40304750204086304},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07710301876068115},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2815770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2815770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5ce4993ed5364ba5af20f2eb18d7c640","is_oa":true,"landing_page_url":"https://doaj.org/article/5ce4993ed5364ba5af20f2eb18d7c640","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 29297-29305 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2815770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2815770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5526962619","display_name":null,"funder_award_id":"2015ZDXX0801A01","funder_id":"https://openalex.org/F4320338074","funder_display_name":"Government of Shandong Province"},{"id":"https://openalex.org/G6130993351","display_name":null,"funder_award_id":"2016GGX101009","funder_id":"https://openalex.org/F4320338074","funder_display_name":"Government of Shandong Province"},{"id":"https://openalex.org/G6349798659","display_name":null,"funder_award_id":"14.756.31.0001","funder_id":"https://openalex.org/F4320321912","funder_display_name":"Ministry of Education and Science of the Russian Federation"},{"id":"https://openalex.org/G712376185","display_name":null,"funder_award_id":"2017JC013","funder_id":"https://openalex.org/F4320311026","funder_display_name":"Shandong University"},{"id":"https://openalex.org/G7551523859","display_name":null,"funder_award_id":"2017CXGC1504","funder_id":"https://openalex.org/F4320338074","funder_display_name":"Government of Shandong Province"},{"id":"https://openalex.org/G7983443448","display_name":null,"funder_award_id":"JQ201718","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320311026","display_name":"Shandong University","ror":"https://ror.org/0207yh398"},{"id":"https://openalex.org/F4320321912","display_name":"Ministry of Education and Science of the Russian Federation","ror":"https://ror.org/00ghqgy32"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320338074","display_name":"Government of Shandong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1544320366","https://openalex.org/W1798945469","https://openalex.org/W1963826206","https://openalex.org/W1978219056","https://openalex.org/W1993482030","https://openalex.org/W1995406764","https://openalex.org/W1998039677","https://openalex.org/W2013912476","https://openalex.org/W2016526558","https://openalex.org/W2017360386","https://openalex.org/W2019974878","https://openalex.org/W2024165284","https://openalex.org/W2036439084","https://openalex.org/W2042086769","https://openalex.org/W2066373878","https://openalex.org/W2071631554","https://openalex.org/W2088025933","https://openalex.org/W2099629058","https://openalex.org/W2117539524","https://openalex.org/W2119741678","https://openalex.org/W2121739212","https://openalex.org/W2143593953","https://openalex.org/W2168217710","https://openalex.org/W2238108400","https://openalex.org/W2325276834","https://openalex.org/W2397208740","https://openalex.org/W2473393247","https://openalex.org/W2513466817","https://openalex.org/W2514763871","https://openalex.org/W2560356199","https://openalex.org/W2563105712","https://openalex.org/W6638060716","https://openalex.org/W6712697978","https://openalex.org/W6725731939"],"related_works":["https://openalex.org/W2120164251","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081"],"abstract_inverted_index":{"Functional":[0],"magnetic":[1],"resonance":[2],"imaging":[3],"(fMRI)":[4],"has":[5],"increasingly":[6],"come":[7],"to":[8,39,91,109,139],"dominate":[9],"brain":[10,20],"mapping":[11],"research,":[12],"as":[13],"it":[14,149],"provides":[15],"a":[16,81,86,111,119,151,160,172],"dynamic":[17],"view":[18],"of":[19,35,48,58,62,73,122,133,163,169],"matter.":[21],"Feature":[22],"selection":[23],"or":[24],"extraction":[25],"methods":[26,188],"play":[27],"an":[28,191],"important":[29],"role":[30],"in":[31,171],"the":[32,46,49,60,67,93,99,131,144,167],"successful":[33],"application":[34],"machine":[36],"learning":[37],"techniques":[38],"classifying":[40],"fMRI":[41,53,101,146,157,196],"data":[42,54,158],"by":[43],"appropriately":[44],"reducing":[45],"dimensionality":[47,63,134],"data.":[50,102,147,197],"While":[51],"whole-brain":[52,100,145],"contains":[55],"large":[56,120,161],"numbers":[57,162],"voxels,":[59,164],"curse":[61,132],"problem":[64],"may":[65],"limit":[66],"feature":[68],"selection/extraction":[69],"and":[70,95,113,117,136],"classification":[71,181],"performance":[72],"traditional":[74,187],"methods.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79],"propose":[80],"novel":[82],"framework":[83,128,182],"based":[84,183,189],"on":[85,184,190],"tensor":[87,104],"neural":[88,115,173],"network":[89,116,123],"(TensorNet)":[90],"extract":[92,140],"essential":[94],"discriminative":[96],"features":[97],"from":[98,143],"The":[103,126],"train":[105],"model":[106],"was":[107],"employed":[108],"construct":[110],"simple":[112],"shallow":[114],"compress":[118],"number":[121,168],"weight":[124],"parameters.":[125],"proposed":[127,180],"can":[129],"avoid":[130],"problem,":[135],"allow":[137],"us":[138],"effective":[141],"patterns":[142],"Furthermore,":[148],"reveals":[150],"new":[152],"perspective":[153],"for":[154,194],"analyzing":[155],"complex":[156],"with":[159],"through":[165],"compressing":[166],"parameters":[170],"network.":[174],"Experimental":[175],"results":[176],"confirmed":[177],"that":[178],"our":[179],"TensorNet":[185],"outperforms":[186],"SVM":[192],"classifier":[193],"multi-class":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
