{"id":"https://openalex.org/W4382752264","doi":"https://doi.org/10.1109/access.2023.3291352","title":"Atrial Fibrillation Detection Algorithm Based on Graph Convolution Network","display_name":"Atrial Fibrillation Detection Algorithm Based on Graph Convolution Network","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4382752264","doi":"https://doi.org/10.1109/access.2023.3291352"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3291352","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3291352","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10168903.pdf","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://ieeexplore.ieee.org/ielx7/6287639/6514899/10168903.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070922232","display_name":"Hua Ma","orcid":"https://orcid.org/0000-0001-7132-9258"},"institutions":[{"id":"https://openalex.org/I4210152160","display_name":"Zhengzhou Railway Vocational & Technical College","ror":"https://ror.org/04zs83x19","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Ma","raw_affiliation_strings":["Henan High-Speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","Henan High-speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan High-Speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","institution_ids":["https://openalex.org/I4210152160"]},{"raw_affiliation_string":"Henan High-speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","institution_ids":["https://openalex.org/I4210152160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052358046","display_name":"Lingnan Xia","orcid":"https://orcid.org/0000-0003-3525-5647"},"institutions":[{"id":"https://openalex.org/I4210152160","display_name":"Zhengzhou Railway Vocational & Technical College","ror":"https://ror.org/04zs83x19","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingnan Xia","raw_affiliation_strings":["Henan High-Speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","Henan High-speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3525-5647","affiliations":[{"raw_affiliation_string":"Henan High-Speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","institution_ids":["https://openalex.org/I4210152160"]},{"raw_affiliation_string":"Henan High-speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China","institution_ids":["https://openalex.org/I4210152160"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210152160"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.6024,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.94403631,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"67191","last_page":"67200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9244999885559082,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"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":0.6789575219154358},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.564671516418457},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5134357213973999},{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"Atrial fibrillation","score":0.5125179290771484},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4948961138725281},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24212390184402466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2413778007030487},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.11953884363174438},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1003744900226593}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6789575219154358},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.564671516418457},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5134357213973999},{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.5125179290771484},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4948961138725281},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24212390184402466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2413778007030487},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.11953884363174438},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1003744900226593},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3291352","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3291352","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10168903.pdf","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:a3aa4089213c4af98913f2c16a345dd7","is_oa":true,"landing_page_url":"https://doaj.org/article/a3aa4089213c4af98913f2c16a345dd7","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 11, Pp 67191-67200 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3291352","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3291352","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10168903.pdf","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":[],"awards":[{"id":"https://openalex.org/G1792714677","display_name":null,"funder_award_id":"222102220105","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"}],"funders":[{"id":"https://openalex.org/F4320336593","display_name":"Henan Provincial Science and Technology Research Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4382752264.pdf","grobid_xml":"https://content.openalex.org/works/W4382752264.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1854569936","https://openalex.org/W1944792747","https://openalex.org/W1981594654","https://openalex.org/W1990479281","https://openalex.org/W1993723007","https://openalex.org/W2027774888","https://openalex.org/W2076151226","https://openalex.org/W2094144838","https://openalex.org/W2097117768","https://openalex.org/W2097201053","https://openalex.org/W2109692256","https://openalex.org/W2122763650","https://openalex.org/W2126913938","https://openalex.org/W2140005438","https://openalex.org/W2155103273","https://openalex.org/W2170605288","https://openalex.org/W2338162851","https://openalex.org/W2605056515","https://openalex.org/W2761605926","https://openalex.org/W2771148491","https://openalex.org/W2782937317","https://openalex.org/W2795086889","https://openalex.org/W2795102241","https://openalex.org/W2798102740","https://openalex.org/W2809343047","https://openalex.org/W2886982273","https://openalex.org/W2898996319","https://openalex.org/W2902644322","https://openalex.org/W2942231644","https://openalex.org/W2962680400","https://openalex.org/W2963757395","https://openalex.org/W2972744877","https://openalex.org/W2984361358","https://openalex.org/W3005111505","https://openalex.org/W3032123378","https://openalex.org/W3082027710","https://openalex.org/W3108118546","https://openalex.org/W3120644354","https://openalex.org/W3127069934","https://openalex.org/W3131332306","https://openalex.org/W3131617710","https://openalex.org/W3133059474","https://openalex.org/W3138479716","https://openalex.org/W3164046276","https://openalex.org/W3192159009","https://openalex.org/W3196099942","https://openalex.org/W3208506679","https://openalex.org/W3210000721","https://openalex.org/W4206822016","https://openalex.org/W4206998764","https://openalex.org/W4220662349","https://openalex.org/W4286304037","https://openalex.org/W4321113904","https://openalex.org/W4321608130","https://openalex.org/W4327908711","https://openalex.org/W4382239624","https://openalex.org/W6674775767","https://openalex.org/W6678515387","https://openalex.org/W6748856961","https://openalex.org/W6750777584","https://openalex.org/W6773935867"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2916669046","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2802841177","https://openalex.org/W2358668433","https://openalex.org/W2047263140","https://openalex.org/W2518330835"],"abstract_inverted_index":{"Atrial":[0],"fibrillation":[1],"(AF)":[2],"is":[3,17,77,155],"a":[4,10,72,112,129],"common":[5],"type":[6],"of":[7,83,96,138,146,152,184,207],"arrhythmia":[8],"with":[9,31,68,74],"high":[11],"incidence":[12],"and":[13,15,49,61,81,87,149,181,204,216,229,237],"risk,":[14],"it":[16],"difficult":[18],"to":[19,158,171],"monitor.":[20],"Deep":[21],"learning-based":[22],"algorithms":[23],"for":[24,40,99],"AF":[25,41,100,114,232],"detection":[26,101,115,233],"have":[27,104],"made":[28],"preliminary":[29],"progress,":[30],"Recurrent":[32,62],"Convolution":[33,53,199],"Neural":[34,54,63],"Networks":[35],"(RCNN)":[36],"being":[37],"widely":[38,230],"used":[39],"detection.":[42],"The":[43,135,243],"RCNN":[44],"algorithm":[45,116],"combines":[46],"ECG":[47,84,88,186,209],"morphology":[48],"rhythm":[50,69,85,182],"information,":[51],"where":[52],"Network":[55,64,200],"(CNN)":[56],"mainly":[57,66],"processes":[58],"morphological":[59,89,144,173,179,203],"features":[60,86,90,98,137,206],"(RNN)":[65],"deals":[67],"information.":[70],"However,":[71],"problem":[73],"this":[75,109],"method":[76,225],"that":[78,246],"direct":[79],"splicing":[80],"fusion":[82],"cannot":[91],"fully":[92],"exploit":[93],"the":[94,139,143,150,153,159,167,172,178,185,197,202,208],"information":[95,145,180,183],"both":[97],"because":[102],"they":[103],"different":[105],"representative":[106],"spaces.":[107],"Therefore,":[108,177],"paper":[110],"proposes":[111],"novel":[113],"based":[117],"on":[118,226],"graph":[119,130,141],"convolution":[120],"network,":[121],"named":[122],"AF-GCN.":[123],"First,":[124],"we":[125,165],"transform":[126],"heartbeats":[127],"into":[128],"structure,":[131],"called":[132],"heartbeat":[133,140,154],"diagrams.":[134],"node":[136],"are":[142],"each":[147],"heartbeat,":[148],"edge":[151,168],"linked":[156],"according":[157,170],"time":[160],"interval":[161],"between":[162,175],"heartbeats.":[163,176],"Moreover,":[164],"calculate":[166],"weight":[169],"similarity":[174],"signal":[187,210],"can":[188,211],"be":[189,212],"unifiedly":[190],"expressed":[191],"in":[192,218],"one":[193,219],"heartbeat.":[194],"Then,":[195],"using":[196],"Graph":[198],"(GCN),":[201],"rhythmic":[205],"effectively":[213],"extracted,":[214],"modeled,":[215],"fused":[217],"network":[220],"modal.We":[221],"evaluated":[222],"our":[223],"AF-GCN":[224,247],"two":[227],"popular":[228],"recognized":[231],"benchmarks,":[234],"MIT-BIH":[235],"AFDB":[236,241],"Physionet":[238],"Challenge":[239],"2017":[240],"datasets.":[242],"results":[244],"show":[245],"outperforms":[248],"other":[249],"existing":[250],"methods.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}