{"id":"https://openalex.org/W2914389736","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633163","title":"A Deep Multi-Scale Convolutional Neural Network for Classifying Heartbeats","display_name":"A Deep Multi-Scale Convolutional Neural Network for Classifying Heartbeats","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2914389736","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633163","mag":"2914389736"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5077561806","display_name":"Mengyao Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mengyao Bai","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020075801","display_name":"Yongjun Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongjun Xu","raw_affiliation_strings":["Technology Department Nalong Technology Co. Ltd, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Technology Department Nalong Technology Co. Ltd, Nanjing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024911662","display_name":"Lianyan Wang","orcid":"https://orcid.org/0000-0002-4421-0128"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianyan Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070343691","display_name":"Zhihui Wei","orcid":"https://orcid.org/0000-0002-4841-6051"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Wei","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077561806"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.30649613,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"26","issue":null,"first_page":"1","last_page":"5"},"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":0.9979000091552734,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/computer-science","display_name":"Computer science","score":0.8221332430839539},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7432295083999634},{"id":"https://openalex.org/keywords/heartbeat","display_name":"Heartbeat","score":0.7148032188415527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6549270153045654},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6269100904464722},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.595262348651886},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5777550339698792},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5360183119773865},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.508051872253418},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4395114779472351},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4390360116958618},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3994574546813965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8221332430839539},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7432295083999634},{"id":"https://openalex.org/C13852961","wikidata":"https://www.wikidata.org/wiki/Q17021880","display_name":"Heartbeat","level":2,"score":0.7148032188415527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6549270153045654},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6269100904464722},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.595262348651886},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5777550339698792},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5360183119773865},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.508051872253418},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4395114779472351},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4390360116958618},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3994574546813965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1988183757","https://openalex.org/W1996894363","https://openalex.org/W1998322473","https://openalex.org/W2017487767","https://openalex.org/W2063923412","https://openalex.org/W2087935847","https://openalex.org/W2095409369","https://openalex.org/W2097117768","https://openalex.org/W2100537461","https://openalex.org/W2101166342","https://openalex.org/W2103308415","https://openalex.org/W2108396267","https://openalex.org/W2114842946","https://openalex.org/W2134144792","https://openalex.org/W2148921897","https://openalex.org/W2160094351","https://openalex.org/W2162693370","https://openalex.org/W2194775991","https://openalex.org/W2333414777","https://openalex.org/W2423609858","https://openalex.org/W2552926193","https://openalex.org/W2731010577","https://openalex.org/W2748902594","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6717396565"],"related_works":["https://openalex.org/W4385543909","https://openalex.org/W3039320222","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W2964954556","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0],"electrocardiogram":[1],"(ECG)":[2],"is":[3,62,77,84,160],"a":[4,33],"very":[5],"important":[6],"tool":[7],"to":[8,48,90,138],"reflect":[9],"the":[10,13,49,55,59,64,69,92,97,113,118,123,131,147,155,158,164],"health":[11],"of":[12,54,58,74,94,166],"human":[14],"heart.":[15],"There":[16],"are":[17,88],"many":[18],"cardiac":[19],"abnormalities":[20],"which":[21,40,76,162],"can":[22,41],"be":[23],"diagnosed":[24],"from":[25],"ECG":[26,43,142],"data.":[27],"In":[28,144],"our":[29],"paper,":[30],"we":[31,102],"design":[32],"15-layer":[34],"multi-scale":[35,65,119],"convolutional":[36],"neural":[37],"network":[38,70,98],"(CNN)":[39],"map":[42],"data":[44],"and":[45,109,140],"RR":[46,104],"intervals":[47],"corresponding":[50],"rhythm":[51],"classes.":[52],"One":[53],"key":[56,82],"points":[57],"proposed":[60],"model":[61,121],"that":[63,85],"convolution":[66],"block":[67],"enables":[68],"extract":[71],"scale-relevant":[72],"features":[73,108,115,126],"heartbeats,":[75],"effective":[78],"in":[79,154],"practice.":[80],"Another":[81],"point":[83],"shortcut":[86],"connections":[87],"employed":[89],"avoid":[91],"loss":[93],"information":[95],"as":[96,106,122],"depth":[99],"increases.":[100],"Furthermore,":[101],"employ":[103],"interval":[105],"dynamic":[107],"concatenate":[110],"them":[111],"with":[112],"morphological":[114],"extracted":[116],"by":[117],"CNN":[120],"final":[124],"heartbeat":[125],"for":[127],"classification.":[128],"We":[129],"use":[130],"open":[132],"source":[133],"PhysioBank":[134],"MIT-BIH":[135],"Arrhythmia":[136],"database":[137],"train":[139],"evaluate":[141],"algorithms.":[143],"\u201cclass-based\u201d":[145],"strategy,":[146,157],"recognition":[148],"accuracy":[149,159],"rate":[150],"reaches":[151],"98.32%,":[152],"while":[153],"\u201csubject-based\u201d":[156],"93.9%,":[161],"exceed":[163],"performance":[165],"most":[167],"existing":[168],"classification":[169],"methods.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
