{"id":"https://openalex.org/W3015434240","doi":"https://doi.org/10.1109/icassp40776.2020.9053307","title":"Reversal No Longer Matters: Attention-Based Arrhythmia Detection with Lead-Reversal ECG Data","display_name":"Reversal No Longer Matters: Attention-Based Arrhythmia Detection with Lead-Reversal ECG Data","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015434240","doi":"https://doi.org/10.1109/icassp40776.2020.9053307","mag":"3015434240"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5029024939","display_name":"Zheng Cao","orcid":"https://orcid.org/0000-0002-1565-3683"},"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":"Zheng Cao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102929174","display_name":"Jialin Shi","orcid":"https://orcid.org/0000-0001-9629-3706"},"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":"Jialin Shi","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014958566","display_name":"Ji Wu","orcid":"https://orcid.org/0000-0001-6170-726X"},"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":"Ji Wu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029024939"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.1494,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49483739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"132","issue":null,"first_page":"951","last_page":"955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9983000159263611,"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":0.9945999979972839,"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/lead","display_name":"Lead (geology)","score":0.7277113199234009},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6913121938705444},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6634038686752319},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5115659832954407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.500328779220581},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4918639659881592},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48721712827682495},{"id":"https://openalex.org/keywords/electrocardiography","display_name":"Electrocardiography","score":0.4480399191379547},{"id":"https://openalex.org/keywords/cardiac-arrhythmia","display_name":"Cardiac arrhythmia","score":0.4425605237483978},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3658902645111084},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3341596722602844},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.23087438941001892},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1496926248073578},{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"Atrial fibrillation","score":0.06864705681800842}],"concepts":[{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.7277113199234009},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6913121938705444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6634038686752319},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5115659832954407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.500328779220581},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4918639659881592},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48721712827682495},{"id":"https://openalex.org/C2780040984","wikidata":"https://www.wikidata.org/wiki/Q79785","display_name":"Electrocardiography","level":2,"score":0.4480399191379547},{"id":"https://openalex.org/C2988455589","wikidata":"https://www.wikidata.org/wiki/Q189331","display_name":"Cardiac arrhythmia","level":3,"score":0.4425605237483978},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3658902645111084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3341596722602844},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.23087438941001892},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1496926248073578},{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.06864705681800842},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":26,"referenced_works":["https://openalex.org/W2016272661","https://openalex.org/W2037564104","https://openalex.org/W2070262037","https://openalex.org/W2129392953","https://openalex.org/W2159738997","https://openalex.org/W2194775991","https://openalex.org/W2277019862","https://openalex.org/W2465131110","https://openalex.org/W2482102801","https://openalex.org/W2538883206","https://openalex.org/W2612184698","https://openalex.org/W2767978081","https://openalex.org/W2794550444","https://openalex.org/W2794605122","https://openalex.org/W2794633590","https://openalex.org/W2806806521","https://openalex.org/W2807367691","https://openalex.org/W2807586294","https://openalex.org/W2884697329","https://openalex.org/W2901226889","https://openalex.org/W2902644322","https://openalex.org/W2955058313","https://openalex.org/W2963403868","https://openalex.org/W3103811943","https://openalex.org/W4385245566","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4255463199","https://openalex.org/W4281691423","https://openalex.org/W2411039299","https://openalex.org/W1856410221","https://openalex.org/W2318949977","https://openalex.org/W2334139353","https://openalex.org/W4243014959","https://openalex.org/W2415764305","https://openalex.org/W4254613272","https://openalex.org/W2374523667"],"abstract_inverted_index":{"In":[0,103],"this":[1,69],"paper,":[2],"we":[3,71],"propose":[4],"an":[5],"attention-based":[6],"multi-scale":[7,74],"neural":[8,75],"network":[9,76],"for":[10],"arrhythmia":[11],"detection":[12],"with":[13,18],"lead-reversal":[14,113],"electrocardiogram":[15],"data.":[16],"Electrocardiogram":[17],"a":[19,73,93],"set":[20],"of":[21,37,58,84,97,122],"12":[22],"waveforms(known":[23],"as":[24],"12-lead":[25],"ECG)":[26],"measures":[27],"myocardial":[28],"electro-physiological":[29],"activity,":[30],"which":[31,95,118],"is":[32,90],"important":[33],"in":[34],"clinical":[35],"diagnosis":[36,64],"arrhythmia.":[38],"However,":[39],"lead":[40,85],"reversals":[41],"caused":[42],"by":[43,65],"electrode":[44],"interchange":[45],"may":[46],"cause":[47],"great":[48,120],"interference":[49],"to":[50,54,80],"the":[51,82,105,123],"interpretation,":[52],"leading":[53],"significant":[55],"accuracy":[56],"decline":[57],"automated":[59],"algorithms":[60],"and":[61,115],"possible":[62],"faulty":[63],"cardiologists.":[66],"To":[67],"address":[68],"problem,":[70],"design":[72],"using":[77],"attention":[78],"mechanism":[79],"reduce":[81],"influence":[83],"reversals.":[86],"The":[87],"proposed":[88,106],"model":[89],"evaluated":[91],"on":[92,111],"dataset":[94],"consists":[96],"ECG":[98],"data":[99,114],"from":[100],"3,658":[101],"patients.":[102],"experiments,":[104],"method":[107],"shows":[108],"high":[109],"performance":[110],"both":[112],"normal":[116],"data,":[117],"proves":[119],"robustness":[121],"method.":[124]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}