{"id":"https://openalex.org/W3084557612","doi":"https://doi.org/10.1145/3408127.3408176","title":"A Multi-dilation Convolution Neural Network for Atrial Fibrillation Detection","display_name":"A Multi-dilation Convolution Neural Network for Atrial Fibrillation Detection","publication_year":2020,"publication_date":"2020-06-19","ids":{"openalex":"https://openalex.org/W3084557612","doi":"https://doi.org/10.1145/3408127.3408176","mag":"3084557612"},"language":"en","primary_location":{"id":"doi:10.1145/3408127.3408176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408127.3408176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3408127.3408176","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100768896","display_name":"Yongfeng Huang","orcid":"https://orcid.org/0000-0003-3825-2230"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongfeng Huang","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011995262","display_name":"Jianping Lin","orcid":"https://orcid.org/0000-0001-6930-3104"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Lin","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045183950","display_name":"Guijin Wang","orcid":"https://orcid.org/0000-0002-2131-3044"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guijin Wang","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030488741","display_name":"Zijian Ding","orcid":"https://orcid.org/0000-0002-6372-0369"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Ding","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112382774","display_name":"Li Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Sun","raw_affiliation_strings":["Beijing Xinheyidian Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Beijing Xinheyidian Co., Ltd","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100768896"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.5975,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71201322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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/T10065","display_name":"Atrial Fibrillation Management and Outcomes","score":0.9966999888420105,"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9753999710083008,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.8284976482391357},{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"Atrial fibrillation","score":0.747123658657074},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7010083198547363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6295377612113953},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.5644656419754028},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5579144358634949},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.5069165825843811},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.45537859201431274},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45518654584884644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4464779794216156},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41983562707901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4165405035018921},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.3358246088027954},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2464720606803894},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.13297978043556213},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1303507685661316},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0887698233127594}],"concepts":[{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.8284976482391357},{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.747123658657074},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7010083198547363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6295377612113953},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.5644656419754028},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5579144358634949},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.5069165825843811},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.45537859201431274},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45518654584884644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4464779794216156},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41983562707901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4165405035018921},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3358246088027954},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2464720606803894},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.13297978043556213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1303507685661316},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0887698233127594},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3408127.3408176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408127.3408176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3408127.3408176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408127.3408176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1854569936","https://openalex.org/W1944792747","https://openalex.org/W1974184490","https://openalex.org/W1979686062","https://openalex.org/W1981594654","https://openalex.org/W1990479281","https://openalex.org/W2027774888","https://openalex.org/W2041691167","https://openalex.org/W2076151226","https://openalex.org/W2094144838","https://openalex.org/W2109692256","https://openalex.org/W2122763650","https://openalex.org/W2155103273","https://openalex.org/W2162975087","https://openalex.org/W2170605288","https://openalex.org/W2213630664","https://openalex.org/W2258005604","https://openalex.org/W2338162851","https://openalex.org/W2771148491","https://openalex.org/W2898996319","https://openalex.org/W2902644322"],"related_works":["https://openalex.org/W4229452466","https://openalex.org/W2966276069","https://openalex.org/W2463286374","https://openalex.org/W350273603","https://openalex.org/W2304829496","https://openalex.org/W2052332160","https://openalex.org/W2358307108","https://openalex.org/W2051113792","https://openalex.org/W4287548622","https://openalex.org/W3173347409"],"abstract_inverted_index":{"Atrial":[0,44,76],"fibrillation":[1,45],"(AF)":[2],"is":[3,50,71,121],"the":[4,53,74,102,124],"most":[5],"common":[6],"cardiac":[7],"arrhythmia":[8],"whose":[9],"management":[10],"requires":[11],"long-term":[12],"automatic":[13],"monitoring.":[14],"The":[15,69],"incidence":[16],"of":[17,25,84,93,97,104,118,126],"AF":[18],"increases":[19],"with":[20,52,59,90,112],"age,":[21],"causing":[22],"high":[23],"risks":[24],"stroke":[26],"and":[27,30,79,95],"increased":[28],"morbidity":[29],"mortality.":[31],"In":[32],"this":[33],"article,":[34],"we":[35],"propose":[36],"a":[37,91,114],"multi-dilation":[38,81],"CNN":[39,82],"(convolution":[40],"neural":[41],"network)":[42],"for":[43,123],"detection.":[46],"Our":[47],"proposed":[48],"model":[49,109],"provided":[51],"ability":[54],"to":[55,100],"extract":[56],"multi-scale":[57],"features":[58],"fewer":[60],"parameters":[61],"by":[62],"designing":[63],"MSDC":[64,85],"(multi-scale":[65],"dilation":[66],"convolution)":[67],"blocks.":[68],"evaluation":[70],"performed":[72],"on":[73,132],"MIT-BIH":[75],"Fibrillation":[77],"Database,":[78],"our":[80,108],"composed":[83],"blocks":[86],"outperforms":[87],"other":[88],"methods":[89],"sensitivity":[92],"99.45%":[94],"specificity":[96],"99.61%.":[98],"Compared":[99],"ResNet":[101],"state":[103],"art":[105],"method":[106],"before,":[107],"performs":[110],"better":[111],"only":[113],"quarter":[115],"parameter":[116],"size":[117],"Reset,":[119],"which":[120],"useful":[122],"implementation":[125],"edge":[127],"computing-based":[128],"deep":[129],"learning":[130],"network":[131],"wearable":[133],"ECG":[134],"devices.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}