{"id":"https://openalex.org/W3184299867","doi":"https://doi.org/10.1109/jbhi.2021.3100559","title":"Convolutional Neural Network With Sparse Strategies to Classify Dynamic Functional Connectivity","display_name":"Convolutional Neural Network With Sparse Strategies to Classify Dynamic Functional Connectivity","publication_year":2021,"publication_date":"2021-07-27","ids":{"openalex":"https://openalex.org/W3184299867","doi":"https://doi.org/10.1109/jbhi.2021.3100559","mag":"3184299867","pmid":"https://pubmed.ncbi.nlm.nih.gov/34314368"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2021.3100559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3100559","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035117617","display_name":"Junzhong Ji","orcid":"https://orcid.org/0000-0001-6951-741X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junzhong Ji","raw_affiliation_strings":["Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6951-741X","affiliations":[{"raw_affiliation_string":"Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101589085","display_name":"Zhihui Chen","orcid":"https://orcid.org/0000-0003-0175-0404"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Chen","raw_affiliation_strings":["Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0175-0404","affiliations":[{"raw_affiliation_string":"Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083745549","display_name":"Cuicui Yang","orcid":"https://orcid.org/0000-0002-4471-7447"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuicui Yang","raw_affiliation_strings":["Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4471-7447","affiliations":[{"raw_affiliation_string":"Beijing Artificial Intelligence Institute, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":1.0376,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.7371982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"26","issue":"3","first_page":"1219","last_page":"1228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9850000143051147,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8263260126113892},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7040345668792725},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7018942832946777},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6827479004859924},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6639113426208496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6587470769882202},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5882482528686523},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43562132120132446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3415601849555969},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2576141953468323}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8263260126113892},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7040345668792725},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7018942832946777},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6827479004859924},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6639113426208496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6587470769882202},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5882482528686523},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43562132120132446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3415601849555969},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2576141953468323}],"mesh":[{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001931","descriptor_name":"Brain Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D001931","descriptor_name":"Brain Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D001931","descriptor_name":"Brain Mapping","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2021.3100559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3100559","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:34314368","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34314368","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":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1552598564","https://openalex.org/W1560723556","https://openalex.org/W1976623182","https://openalex.org/W2058046532","https://openalex.org/W2092872141","https://openalex.org/W2120759354","https://openalex.org/W2167868121","https://openalex.org/W2170702893","https://openalex.org/W2304527985","https://openalex.org/W2314945771","https://openalex.org/W2412178966","https://openalex.org/W2526511911","https://openalex.org/W2590651237","https://openalex.org/W2725237741","https://openalex.org/W2744921996","https://openalex.org/W2746450741","https://openalex.org/W2752558629","https://openalex.org/W2765216222","https://openalex.org/W2789958560","https://openalex.org/W2791956678","https://openalex.org/W2803793592","https://openalex.org/W2807683509","https://openalex.org/W2884781986","https://openalex.org/W2889325467","https://openalex.org/W2893389247","https://openalex.org/W2896337276","https://openalex.org/W2898352483","https://openalex.org/W2908835407","https://openalex.org/W2913713055","https://openalex.org/W2914502083","https://openalex.org/W2938235323","https://openalex.org/W2945174435","https://openalex.org/W2949980035","https://openalex.org/W2969299904","https://openalex.org/W2979539233","https://openalex.org/W2988958536","https://openalex.org/W3030790048","https://openalex.org/W3048602393","https://openalex.org/W3112952980","https://openalex.org/W4244883719"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W3040691452","https://openalex.org/W2964954556","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Classification":[0],"of":[1,24,80,93,123,134,157],"dynamic":[2],"functional":[3,170],"connectivity":[4],"(DFC)":[5],"is":[6,49,70,87,117],"becoming":[7],"a":[8,32,83,153],"promising":[9],"approach":[10],"for":[11],"diagnosing":[12],"various":[13],"neurodegenerative":[14],"diseases.":[15],"However,":[16],"the":[17,22,56,61,67,75,91,94,107,121,124,132,149,167],"existing":[18],"methods":[19],"generally":[20],"face":[21],"problem":[23],"overfitting.":[25],"To":[26],"solve":[27],"it,":[28],"this":[29],"paper":[30],"proposes":[31],"convolutional":[33,85],"neural":[34],"network":[35],"with":[36,64,160],"three":[37],"sparse":[38,53,95,114],"strategies":[39],"named":[40],"SCNN":[41,135],"to":[42,51,73,89,119,136],"classify":[43],"DFC.":[44,81],"Firstly,":[45],"an":[46,112],"element-wise":[47],"filter":[48,86],"designed":[50],"impose":[52],"constraints":[54],"on":[55,142],"DFC":[57,68,96,158],"matrix":[58,69],"by":[59],"replacing":[60],"redundant":[62],"elements":[63,105],"zeroes,":[65],"where":[66],"specially":[71],"constructed":[72],"quantify":[74],"spatial":[76],"and":[77,98,164],"temporal":[78],"variation":[79],"Secondly,":[82],"1\u00d71":[84],"adopted":[88],"reduce":[90],"dimensionality":[92],"matrix,":[97],"remove":[99],"meaningless":[100],"features":[101],"resulted":[102],"from":[103],"zero":[104],"in":[106],"subsequent":[108],"convolution":[109],"process.":[110],"Finally,":[111],"extra":[113],"optimization":[115],"classifier":[116],"employed":[118],"optimize":[120],"parameters":[122],"above":[125],"two":[126],"filters,":[127],"which":[128],"can":[129,165],"effectively":[130],"improve":[131],"ability":[133],"extract":[137],"discriminative":[138],"features.":[139],"Experimental":[140],"results":[141],"multiple":[143],"resting-state":[144],"fMRI":[145],"datasets":[146],"demonstrate":[147],"that":[148],"proposed":[150],"model":[151],"provides":[152],"better":[154],"classification":[155],"performance":[156],"compared":[159],"several":[161],"state-of-the-art":[162],"methods,":[163],"identify":[166],"abnormal":[168],"brain":[169],"connectivity.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
