{"id":"https://openalex.org/W3076997392","doi":"https://doi.org/10.1109/access.2020.3016938","title":"A Deep Biometric Recognition and Diagnosis Network With Residual Learning for Arrhythmia Screening Using Electrocardiogram Recordings","display_name":"A Deep Biometric Recognition and Diagnosis Network With Residual Learning for Arrhythmia Screening Using Electrocardiogram Recordings","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3076997392","doi":"https://doi.org/10.1109/access.2020.3016938","mag":"3076997392"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3016938","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3016938","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09169638.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/8948470/09169638.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101802747","display_name":"Hao Dang","orcid":"https://orcid.org/0000-0003-1009-8200"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Dang","raw_affiliation_strings":["Engineering Research Center of Information Network, Ministry of Education, Beijing, China","School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1009-8200","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Information Network, Ministry of Education, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020223528","display_name":"Yaru Yue","orcid":"https://orcid.org/0000-0002-1368-0928"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaru Yue","raw_affiliation_strings":["Engineering Research Center of Information Network, Ministry of Education, Beijing, China","School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Information Network, Ministry of Education, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054518292","display_name":"Danqun Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088329","display_name":"Jiading District Central Hospital","ror":"https://ror.org/004j26v17","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210088329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danqun Xiong","raw_affiliation_strings":["Department of Cardiology, Jiading District Central Hospital Affiliated Shanghai University of Medical and Health Sciences, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cardiology, Jiading District Central Hospital Affiliated Shanghai University of Medical and Health Sciences, Shanghai, China","institution_ids":["https://openalex.org/I4210088329"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101815043","display_name":"Xiaoguang Zhou","orcid":"https://orcid.org/0000-0002-1829-927X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Zhou","raw_affiliation_strings":["Engineering Research Center of Information Network, Ministry of Education, Beijing, China","School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Information Network, Ministry of Education, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043401373","display_name":"Xiangdong Xu","orcid":"https://orcid.org/0000-0002-7532-243X"},"institutions":[{"id":"https://openalex.org/I4210088329","display_name":"Jiading District Central Hospital","ror":"https://ror.org/004j26v17","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210088329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Xu","raw_affiliation_strings":["Department of Cardiology, Jiading District Central Hospital Affiliated Shanghai University of Medical and Health Sciences, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cardiology, Jiading District Central Hospital Affiliated Shanghai University of Medical and Health Sciences, Shanghai, China","institution_ids":["https://openalex.org/I4210088329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049261977","display_name":"Xingxiang Tao","orcid":"https://orcid.org/0000-0003-2112-0469"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingxiang Tao","raw_affiliation_strings":["Engineering Research Center of Information Network, Ministry of Education, Beijing, China","School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2112-0469","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Information Network, Ministry of Education, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0676,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.79979673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"153436","last_page":"153454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":1.0,"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":1.0,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9973000288009644,"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9868999719619751,"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/deep-learning","display_name":"Deep learning","score":0.790580689907074},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7649896740913391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7279212474822998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7176423072814941},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6454063057899475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5970931649208069},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5576639175415039},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.553155243396759},{"id":"https://openalex.org/keywords/cardiac-arrhythmia","display_name":"Cardiac arrhythmia","score":0.5530746579170227},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5183223485946655},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4798264503479004},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44398295879364014},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.42063191533088684},{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"Atrial fibrillation","score":0.415994793176651},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3502100110054016},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.18853983283042908},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14952096343040466},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0965372622013092},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06629213690757751}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.790580689907074},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7649896740913391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7279212474822998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7176423072814941},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6454063057899475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5970931649208069},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5576639175415039},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.553155243396759},{"id":"https://openalex.org/C2988455589","wikidata":"https://www.wikidata.org/wiki/Q189331","display_name":"Cardiac arrhythmia","level":3,"score":0.5530746579170227},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5183223485946655},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4798264503479004},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44398295879364014},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.42063191533088684},{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.415994793176651},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3502100110054016},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.18853983283042908},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14952096343040466},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0965372622013092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06629213690757751},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3016938","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3016938","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09169638.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a11fa811e8724ae091e055e3bd07d97b","is_oa":true,"landing_page_url":"https://doaj.org/article/a11fa811e8724ae091e055e3bd07d97b","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 8, Pp 153436-153454 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3016938","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3016938","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09169638.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G7470181681","display_name":null,"funder_award_id":"B08004","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"}],"funders":[{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3076997392.pdf","grobid_xml":"https://content.openalex.org/works/W3076997392.grobid-xml"},"referenced_works_count":75,"referenced_works":["https://openalex.org/W596238075","https://openalex.org/W639708223","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1975640002","https://openalex.org/W1984944288","https://openalex.org/W2004475192","https://openalex.org/W2004896487","https://openalex.org/W2011658861","https://openalex.org/W2035381272","https://openalex.org/W2060094658","https://openalex.org/W2064493351","https://openalex.org/W2074187626","https://openalex.org/W2076063813","https://openalex.org/W2104614052","https://openalex.org/W2115959656","https://openalex.org/W2162800060","https://openalex.org/W2194775991","https://openalex.org/W2251133041","https://openalex.org/W2291961022","https://openalex.org/W2338769309","https://openalex.org/W2418674135","https://openalex.org/W2482102801","https://openalex.org/W2532338198","https://openalex.org/W2560023338","https://openalex.org/W2584523837","https://openalex.org/W2585488429","https://openalex.org/W2601564443","https://openalex.org/W2610751394","https://openalex.org/W2630837129","https://openalex.org/W2748902594","https://openalex.org/W2761286016","https://openalex.org/W2792396409","https://openalex.org/W2795302640","https://openalex.org/W2799012717","https://openalex.org/W2800884944","https://openalex.org/W2802480283","https://openalex.org/W2805227459","https://openalex.org/W2829536470","https://openalex.org/W2885127939","https://openalex.org/W2891342985","https://openalex.org/W2895109358","https://openalex.org/W2911154021","https://openalex.org/W2916049207","https://openalex.org/W2937260742","https://openalex.org/W2942497026","https://openalex.org/W2950800384","https://openalex.org/W2951307174","https://openalex.org/W2951632519","https://openalex.org/W2961638199","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963596856","https://openalex.org/W2963794516","https://openalex.org/W2969929892","https://openalex.org/W2972178360","https://openalex.org/W2974804109","https://openalex.org/W2987876617","https://openalex.org/W2988190049","https://openalex.org/W2989431519","https://openalex.org/W3008792398","https://openalex.org/W3012024716","https://openalex.org/W3099916295","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6677464161","https://openalex.org/W6703646928","https://openalex.org/W6714138976","https://openalex.org/W6717190812","https://openalex.org/W6725739302","https://openalex.org/W6733093770","https://openalex.org/W6737108279","https://openalex.org/W6739696289"],"related_works":["https://openalex.org/W2373577936","https://openalex.org/W4221148444","https://openalex.org/W4387678054","https://openalex.org/W2389596151","https://openalex.org/W3095575180","https://openalex.org/W4306784355","https://openalex.org/W2169308097","https://openalex.org/W4246226292","https://openalex.org/W3091984855","https://openalex.org/W2150768546"],"abstract_inverted_index":{"Arrhythmia":[0],"is":[1,14,31],"one":[2],"of":[3,82,107,111,120,178,204,209],"the":[4,11,80,88,118,121,138,143,165,186,201,205,239],"most":[5],"persistent":[6],"chronic":[7],"heart":[8],"diseases":[9],"in":[10,75,253],"elderly":[12],"and":[13,19,26,40,65,71,84,96,126,155,176,181,191,218,229],"associated":[15],"with":[16,35,98,188,221],"high":[17],"morbidity":[18],"mortality":[20],"such":[21],"as":[22,246],"stroke,":[23],"cardiac":[24],"failure,":[25],"coronary":[27],"artery":[28],"diseases.":[29],"It":[30],"significant":[32],"for":[33,79,241,250],"patients":[34],"arrhythmias":[36],"to":[37,73,116],"automatically":[38],"detect":[39],"classify":[41],"arrhythmia":[42,83,102],"heartbeats":[43],"using":[44],"electrocardiogram":[45],"(ECG)":[46],"signals.":[47,108,257],"In":[48],"this":[49],"paper,":[50],"we":[51],"develop":[52],"three":[53],"robust":[54],"deep":[55],"convolutional":[56],"neural":[57],"network":[58,64,220],"(DCNN)":[59],"models,":[60],"including":[61],"a":[62,99,161,197,227],"plain-CNN":[63,139],"two":[66],"MSF(multi-scale":[67],"fusion)-CNN":[68],"architectures":[69],"(A":[70],"B),":[72],"aid":[74],"better":[76],"feature":[77,202],"extraction":[78],"detection":[81],"thus":[85],"significantly":[86],"improve":[87,160],"performance":[89,119],"metrics.":[90],"The":[91,123,207],"proposed":[92,215],"models":[93],"are":[94,114,133],"trained":[95],"tested":[97],"public":[100],"MIT-BIH":[101],"database":[103],"on":[104,200,233],"five":[105],"types":[106],"Six":[109],"groups":[110],"ablation":[112,210],"experiments":[113,211],"conducted":[115],"analyze":[117],"models.":[122],"accuracy,":[124,174],"sensitivity,":[125,175],"specificity":[127,177],"obtained":[128],"from":[129,137],"MSF-CNN":[130,168],"architecture":[131,169],"A":[132],"higher":[134],"than":[135],"those":[136],"model,":[140],"demonstrating":[141],"that":[142,213],"different":[144],"parallel":[145],"group":[146,193],"convolution":[147,194],"blocks":[148,195],"(1":[149],"\u00d7":[150,153,157],"3,":[151],"1":[152,156],"5,":[154],"7)":[158],"dramatically":[159],"model's":[162],"performance.":[163],"Additionally,":[164],"best":[166],"model":[167],"B":[170],"achieves":[171,226],"an":[172,247],"average":[173],"98.00%,":[179],"96.17%,":[180],"96.38%,":[182],"respectively.":[183],"This":[184],"illustrates":[185],"method":[187],"residual":[189,222],"learning":[190,203,223],"concatenation":[192],"has":[196,238],"profound":[198],"effect":[199],"model.":[206],"results":[208],"show":[212],"our":[214],"biometric":[216],"recognition":[217],"diagnosis":[219,231],"(MSF-CNN":[224],"B)":[225],"rapid":[228],"reliable":[230],"approach":[232],"ECG":[234,255],"signal":[235],"classification,":[236],"which":[237],"potential":[240],"introduction":[242],"into":[243],"clinical":[244],"practice":[245],"excellent":[248],"tool":[249],"aiding":[251],"cardiologists":[252],"reading":[254],"heartbeat":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}