{"id":"https://openalex.org/W4292133360","doi":"https://doi.org/10.1109/jbhi.2022.3199505","title":"Deep Forest With Multi-Channel Message Passing and Neighborhood Aggregation Mechanisms for Brain Network Classification","display_name":"Deep Forest With Multi-Channel Message Passing and Neighborhood Aggregation Mechanisms for Brain Network Classification","publication_year":2022,"publication_date":"2022-08-17","ids":{"openalex":"https://openalex.org/W4292133360","doi":"https://doi.org/10.1109/jbhi.2022.3199505","pmid":"https://pubmed.ncbi.nlm.nih.gov/35976849"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2022.3199505","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3199505","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":["Faculty of Information Technology, Beijing Artificial Intelligence Institute, Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6951-741X","affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Beijing Artificial Intelligence Institute, Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374874","display_name":"Junwei Li","orcid":"https://orcid.org/0000-0002-9620-4491"},"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":"Junwei Li","raw_affiliation_strings":["Faculty of Information Technology, Beijing Artificial Intelligence Institute, Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Beijing Artificial Intelligence Institute, Beijing Municipal Key Laboratory of Multimedia and Intelligent Software 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":0.9038,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71039409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"26","issue":"11","first_page":"5608","last_page":"5618"},"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":0.9994000196456909,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7616448402404785},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6563412547111511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6160483360290527},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5722407698631287},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5362623929977417},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5213190913200378},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5183285474777222},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.4667872190475464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4467940628528595},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.43625426292419434},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3810589909553528},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12407714128494263},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.10503450036048889}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7616448402404785},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6563412547111511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6160483360290527},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5722407698631287},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5362623929977417},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5213190913200378},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5183285474777222},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.4667872190475464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4467940628528595},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.43625426292419434},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3810589909553528},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12407714128494263},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.10503450036048889},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"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":"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":"D065928","descriptor_name":"Forests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D065928","descriptor_name":"Forests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D065928","descriptor_name":"Forests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2022.3199505","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3199505","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:35976849","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35976849","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":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W761823288","https://openalex.org/W1457602677","https://openalex.org/W1560723556","https://openalex.org/W1575960342","https://openalex.org/W1775388063","https://openalex.org/W2056132907","https://openalex.org/W2074957274","https://openalex.org/W2097723363","https://openalex.org/W2127259163","https://openalex.org/W2167868121","https://openalex.org/W2291733379","https://openalex.org/W2314945771","https://openalex.org/W2526511911","https://openalex.org/W2532841108","https://openalex.org/W2590651237","https://openalex.org/W2592340788","https://openalex.org/W2606031557","https://openalex.org/W2606780347","https://openalex.org/W2768990978","https://openalex.org/W2769418009","https://openalex.org/W2787999987","https://openalex.org/W2889669663","https://openalex.org/W2911964244","https://openalex.org/W2924183423","https://openalex.org/W2949143034","https://openalex.org/W2963335520","https://openalex.org/W2972732693","https://openalex.org/W2974016242","https://openalex.org/W2990819629","https://openalex.org/W3005007745","https://openalex.org/W3018025842","https://openalex.org/W3022701104","https://openalex.org/W3044779191","https://openalex.org/W3047442682","https://openalex.org/W3092880557","https://openalex.org/W3118922117","https://openalex.org/W3197550162","https://openalex.org/W3212514517","https://openalex.org/W3216632247","https://openalex.org/W6736685754","https://openalex.org/W6803878253"],"related_works":["https://openalex.org/W4386259002","https://openalex.org/W2978729728","https://openalex.org/W1546989560","https://openalex.org/W3193043704","https://openalex.org/W3171520305","https://openalex.org/W1924178503","https://openalex.org/W4308716060","https://openalex.org/W4280648719","https://openalex.org/W3135126032","https://openalex.org/W3033346322"],"abstract_inverted_index":{"As":[0],"a":[1,19,35,75,117,123],"novel":[2],"deep":[3,6,42,76],"learning":[4,169],"method,":[5],"forest":[7,77],"has":[8],"achieved":[9],"excellent":[10],"classification":[11,191],"performance":[12,192],"on":[13,28,174,190],"many":[14],"small-scale":[15],"datasets,":[16],"thus":[17],"providing":[18],"new":[20],"opportunity":[21],"to":[22,49,57,61,67,88,108,128,165],"accurately":[23,194],"classify":[24],"brain":[25,68,197],"networks":[26,103],"(BNs)":[27],"limited":[29],"fMRI":[30],"data.":[31],"Though":[32],"there":[33],"are":[34,160],"few":[36],"explorations":[37],"about":[38],"classifying":[39],"BNs":[40,54],"using":[41],"forest,":[43],"they":[44],"only":[45],"adopt":[46],"sliding":[47],"windows":[48],"extract":[50,89,130],"adjacent":[51],"features":[52,64,143,159],"of":[53],"and":[55,83,90,105,122,147,170,179,193],"fail":[56],"use":[58,98],"prior":[59],"knowledge":[60],"strengthen":[62],"the":[63,99,106,136,148,157,163,184],"more":[65],"relevant":[66],"diseases.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73,97,115],"propose":[74],"framework":[78],"with":[79],"multi-channel":[80,93,118,132,153],"message":[81,119],"passing":[82,120],"neighborhood":[84,125],"aggregation":[85,126],"mechanisms":[86],"(DF-MCMPNA)":[87],"aggregate":[91],"long-range":[92,131],"topological":[94,133,142,154],"features.":[95,155],"Firstly,":[96],"three":[100],"intrinsic":[101],"connectivity":[102],"(ICNs)":[104],"whole-brain":[107],"form":[109],"four":[110],"feature":[111,168],"extraction":[112],"channels.":[113],"Secondly,":[114],"present":[116],"mechanism":[121,127,138,150],"channel-shared":[124],"recursively":[129],"features,":[134],"where":[135],"first":[137],"can":[139,151],"learn":[140],"local":[141],"in":[144],"each":[145],"channel":[146],"second":[149],"fuse":[152],"Finally,":[156],"extracted":[158],"fed":[161],"into":[162],"casForst":[164],"perform":[166],"further":[167],"classification.":[171],"Experimental":[172],"results":[173],"ABIDE":[175,177],"I,":[176],"II,":[178],"ADHD-200":[180],"datasets":[181],"show":[182],"that":[183],"DF-MCMPNA":[185],"outperforms":[186],"several":[187],"state-of-the-art":[188],"methods":[189],"identifies":[195],"abnormal":[196],"regions.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}