{"id":"https://openalex.org/W3081794611","doi":"https://doi.org/10.1109/embc44109.2020.9175277","title":"aNy-way Independent Component Analysis","display_name":"aNy-way Independent Component Analysis","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3081794611","doi":"https://doi.org/10.1109/embc44109.2020.9175277","mag":"3081794611","pmid":"https://pubmed.ncbi.nlm.nih.gov/33018341"},"language":"en","primary_location":{"id":"doi:10.1109/embc44109.2020.9175277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175277","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8258844","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046846201","display_name":"Kuaikuai Duan","orcid":"https://orcid.org/0000-0002-6008-7393"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]},{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]},{"id":"https://openalex.org/I4210133909","display_name":"Center for Translational Research in Neuroimaging and Data Science","ror":"https://ror.org/02qx6zf82","country_code":"US","type":"facility","lineage":["https://openalex.org/I130701444","https://openalex.org/I150468666","https://openalex.org/I181565077","https://openalex.org/I4210133909"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuaikuai Duan","raw_affiliation_strings":["Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444","https://openalex.org/I150468666","https://openalex.org/I181565077","https://openalex.org/I4210133909"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032850756","display_name":"Vince D. Calhoun","orcid":"https://orcid.org/0000-0001-9058-0747"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vince D. Calhoun","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424748","display_name":"Jingyu Liu","orcid":"https://orcid.org/0000-0002-1724-7523"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingyu Liu","raw_affiliation_strings":["Department of Psychology, Georgia State University, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Psychology, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024260846","display_name":"Rogers F. Silva","orcid":"https://orcid.org/0000-0002-7271-1288"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rogers F. Silva","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2020","issue":null,"first_page":"1770","last_page":"1774"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.6995283365249634},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5402969121932983},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.5102553367614746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12597110867500305},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0711166262626648}],"concepts":[{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.6995283365249634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5402969121932983},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.5102553367614746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12597110867500305},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0711166262626648},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D015999","descriptor_name":"Multivariate Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015999","descriptor_name":"Multivariate Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015999","descriptor_name":"Multivariate Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/embc44109.2020.9175277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175277","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:33018341","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33018341","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8258844","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8258844","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Annu Int Conf IEEE Eng Med Biol Soc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8258844","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8258844","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Annu Int Conf IEEE Eng Med Biol Soc","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6093993598","display_name":null,"funder_award_id":"R01 MH106655","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1592057812","https://openalex.org/W1596301525","https://openalex.org/W1755563775","https://openalex.org/W2023095826","https://openalex.org/W2029701245","https://openalex.org/W2033128599","https://openalex.org/W2055637322","https://openalex.org/W2108384452","https://openalex.org/W2133069808","https://openalex.org/W2146144468","https://openalex.org/W2149966221","https://openalex.org/W2330647764","https://openalex.org/W2903112826","https://openalex.org/W3092565706","https://openalex.org/W6679756777","https://openalex.org/W6769875533"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4252230435","https://openalex.org/W2121429698","https://openalex.org/W2182042810","https://openalex.org/W55679925","https://openalex.org/W3080404860","https://openalex.org/W2046761971","https://openalex.org/W3144722888","https://openalex.org/W2089650474","https://openalex.org/W2364896863"],"abstract_inverted_index":{"Multimodal":[0],"data":[1,272],"fusion":[2,10,273],"is":[3,62,69],"a":[4,163,183,209,268],"topic":[5],"of":[6,76,100,150,156,167,191,245,256,274,277,285],"great":[7],"interest.":[8],"Several":[9],"methods":[11],"have":[12,239],"been":[13],"proposed":[14],"to":[15,64,73,123,186],"investigate":[16],"coherent":[17],"patterns":[18],"and":[19,42,95,110,117,148,169,193,202,228,252,258,279],"corresponding":[20],"linkages":[21],"across":[22,58,195],"modalities,":[23],"such":[24],"as":[25],"joint":[26],"independent":[27,204],"component":[28],"analysis":[29,34,206],"(jICA),":[30],"multiset":[31],"canonical":[32],"correlation":[33,56,145],"(mCCA),":[35],"mCCA+jICA,":[36,87],"disjoint":[37],"subspace":[38],"using":[39],"ICA":[40,112,142,198,201,222,249],"(DS-ICA)":[41],"parallel":[43,111],"ICA.":[44],"JICA":[45],"exploits":[46],"source":[47,257],"independence":[48,149,190],"but":[49,61,120,230],"assumes":[50,127],"shared":[51,128,210],"loading":[52,129,259],"parameters.":[53],"MCCA":[54],"maximizes":[55,144],"linkage":[57,170,280],"modalities":[59,77,147,168,238,278],"directly":[60],"limited":[63,122,165],"orthogonal":[65],"features.":[66],"While":[67],"there":[68],"no":[70],"theoretical":[71],"limit":[72],"the":[74,84,97,106,189,232,240],"number":[75,99,155,166,244,276,284],"analyzed":[78],"together":[79],"by":[80],"jICA,":[81],"mCCA,":[82],"or":[83,242],"two-step":[85],"approach":[86],"these":[88,177],"approaches":[89],"can":[90,113,172],"only":[91,162,224],"extract":[92],"common":[93,116,132],"features":[94,119],"require":[96],"same":[98,241],"sources/components":[101],"for":[102,158,270,288],"all":[103],"modalities.":[104,125,196,290],"On":[105],"other":[107],"hand,":[108],"DS-ICA":[109,126],"identify":[114],"both":[115],"distinct":[118],"are":[121,139],"two":[124],"parameters":[130],"among":[131],"features,":[133],"which":[134],"works":[135],"well":[136],"when":[137],"links":[138],"strong.":[140],"Parallel":[141],"simultaneously":[143,187],"between":[146],"sources,":[151],"while":[152],"allowing":[153,282],"different":[154,237,243,283,289],"sources":[157,192,227,287],"each":[159],"modality.":[160],"However,":[161],"very":[164],"pairs":[171],"be":[173],"optimized.":[174],"To":[175],"overcome":[176],"limitations,":[178],"we":[179],"propose":[180],"aNy-way":[181,197,221,248],"ICA,":[182],"new":[184],"model":[185,213,269],"maximize":[188],"correlations":[194],"combines":[199],"infomax":[200],"Gaussian":[203],"vector":[205],"(IVA-G)":[207],"via":[208],"weight":[211],"matrix":[212],"without":[214],"orthogonality":[215],"constraints.":[216],"Simulation":[217],"results":[218],"demonstrate":[219],"that":[220],"not":[223],"accurately":[225],"recovers":[226],"loadings,":[229],"also":[231],"true":[233],"covariance/linkage":[234],"patterns,":[235],"whether":[236],"sources.":[246],"Moreover,":[247],"outperforms":[250],"mCCA":[251],"mCCA+jICA":[253],"in":[254],"terms":[255],"recovery":[260],"accuracy,":[261],"especially":[262],"under":[263],"noisy":[264],"conditions.Clinical":[265],"Relevance-This":[266],"establishes":[267],"N-way":[271],"any":[275],"pairs,":[281],"non-orthogonal":[286]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}