{"id":"https://openalex.org/W4388280105","doi":"https://doi.org/10.1109/icbase59196.2023.10303136","title":"Data Fusion-based graph representation learning for brain disease recognition","display_name":"Data Fusion-based graph representation learning for brain disease recognition","publication_year":2023,"publication_date":"2023-08-25","ids":{"openalex":"https://openalex.org/W4388280105","doi":"https://doi.org/10.1109/icbase59196.2023.10303136"},"language":"en","primary_location":{"id":"doi:10.1109/icbase59196.2023.10303136","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icbase59196.2023.10303136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Big Data &amp; Artificial Intelligence &amp; Software Engineering (ICBASE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5113038489","display_name":"Baixue Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baixue Huang","raw_affiliation_strings":["Jiangsu University,School of Computer Science and Communication Engineering,Jiangsu,China","School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu University,School of Computer Science and Communication Engineering,Jiangsu,China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056659804","display_name":"Hu Lu","orcid":"https://orcid.org/0000-0003-0350-4055"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Lu","raw_affiliation_strings":["Jiangsu University,School of Computer Science and Communication Engineering,Jiangsu,China","School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu University,School of Computer Science and Communication Engineering,Jiangsu,China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113038489"],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":null,"apc_paid":null,"fwci":0.1748,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57299757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9599000215530396,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7040355801582336},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6363292932510376},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6244577169418335},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.568286657333374},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.562615156173706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5615407228469849},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5056917667388916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4490337371826172},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41261014342308044},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.4112752676010132},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37152156233787537}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7040355801582336},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6363292932510376},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6244577169418335},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.568286657333374},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.562615156173706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5615407228469849},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5056917667388916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4490337371826172},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41261014342308044},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.4112752676010132},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37152156233787537},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbase59196.2023.10303136","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icbase59196.2023.10303136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Big Data &amp; Artificial Intelligence &amp; Software Engineering (ICBASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2393319904","https://openalex.org/W2742812719","https://openalex.org/W2792059397","https://openalex.org/W2807395493","https://openalex.org/W2964015378","https://openalex.org/W2981450816","https://openalex.org/W3001525933","https://openalex.org/W3003270100","https://openalex.org/W3033039844","https://openalex.org/W3034693603","https://openalex.org/W3040213512","https://openalex.org/W3095479837","https://openalex.org/W3095602948","https://openalex.org/W3095746859","https://openalex.org/W3104425534","https://openalex.org/W3110933490","https://openalex.org/W3133909080","https://openalex.org/W3154503084","https://openalex.org/W3168925038","https://openalex.org/W4214814755","https://openalex.org/W4220907116","https://openalex.org/W4226172857","https://openalex.org/W4282983590","https://openalex.org/W4283796272","https://openalex.org/W4295746671","https://openalex.org/W4296473473","https://openalex.org/W4322614756","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6779518175","https://openalex.org/W6779940601","https://openalex.org/W6784694379","https://openalex.org/W6843063088"],"related_works":["https://openalex.org/W3036264823","https://openalex.org/W3206528106","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W1559483280","https://openalex.org/W2082479932","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Self-supervised":[0],"graph":[1,19,25,108],"learning":[2,27,110],"has":[3],"attracted":[4],"intensive":[5],"attention":[6],"due":[7],"to":[8,10,94],"attempts":[9],"eliminate":[11],"the":[12,23,74,96,121],"need":[13],"for":[14,54],"expensive":[15],"data":[16,119],"labeling,":[17],"especially":[18],"contrastive":[20,26],"learning.":[21],"However,":[22],"existing":[24],"methods":[28],"rely":[29],"heavily":[30],"on":[31,50,114],"selecting":[32],"negative":[33],"samples":[34],"or":[35],"symmetric":[36],"network":[37],"structures.":[38],"To":[39,72],"overcome":[40],"these":[41],"limitations,":[42],"we":[43,80],"propose":[44],"a":[45,90],"Data":[46],"Fusion":[47],"framework":[48],"based":[49],"Graph":[51],"Representation":[52],"Learning":[53],"brain":[55,116],"disease":[56],"recognition":[57],"(DF-GRL),":[58],"which":[59],"integrates":[60],"structure":[61,75],"and":[62,102,123],"attribute":[63,78,86],"information":[64],"extracted":[65],"from":[66],"an":[67],"asymmetric":[68],"dual":[69],"branch":[70],"network.":[71],"explore":[73],"representation":[76,109],"of":[77,85,99,125],"embedding,":[79],"sample":[81],"neighbor":[82,103],"node":[83],"features":[84],"embedding.":[87],"We":[88],"apply":[89],"cross-correlation-based":[91],"loss":[92],"function":[93],"constrain":[95],"structural":[97,100],"consistency":[98],"embedding":[101,104],"representations.":[105],"With":[106],"state-of-the-art":[107],"methods,":[111],"extensive":[112],"experiments":[113],"seven":[115],"functional":[117],"connectivity":[118],"demonstrate":[120],"effectiveness":[122],"efficiency":[124],"our":[126],"method.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
