{"id":"https://openalex.org/W4401906028","doi":"https://doi.org/10.1109/tim.2024.3449956","title":"Lightweight Optimization of Deep Learning Models for Accurate Arrhythmia Detection in Clinical 12-Lead ECG Data","display_name":"Lightweight Optimization of Deep Learning Models for Accurate Arrhythmia Detection in Clinical 12-Lead ECG Data","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401906028","doi":"https://doi.org/10.1109/tim.2024.3449956"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3449956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3449956","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5100700939","display_name":"Yunqing Liu","orcid":"https://orcid.org/0000-0002-4518-1306"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunqing Liu","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4518-1306","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021977927","display_name":"Chengjin Qin","orcid":"https://orcid.org/0000-0002-5200-3241"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjin Qin","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5200-3241","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100301480","display_name":"Yuanyuan Tian","orcid":"https://orcid.org/0000-0003-0913-3144"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Tian","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0913-3144","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034801598","display_name":"M. Wang","orcid":"https://orcid.org/0000-0002-5040-7269"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengxiao Wang","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5040-7269","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022157769","display_name":"Jinlei Liu","orcid":"https://orcid.org/0000-0001-7254-6086"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinlei Liu","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7254-6086","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021632916","display_name":"Yanrui Jin","orcid":"https://orcid.org/0000-0001-9489-5447"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanrui Jin","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2691-9643","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyuan Li","orcid":"https://orcid.org/0000-0003-0470-8762"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Li","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0470-8762","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100551410","display_name":"Liqun Zhao","orcid":"https://orcid.org/0000-0002-2386-5299"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210135742","display_name":"Shanghai First People's Hospital","ror":"https://ror.org/04a46mh28","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210135742"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqun Zhao","raw_affiliation_strings":["Department of Cardiology, Shanghai First People&#x2019;s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2386-5299","affiliations":[{"raw_affiliation_string":"Department of Cardiology, Shanghai First People&#x2019;s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I4210135742","https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108555426","display_name":"Chengliang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengliang Liu","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6754-258X","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5100700939"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.1673,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.814067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"17"},"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":0.9944999814033508,"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":0.9675999879837036,"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":0.5892822742462158},{"id":"https://openalex.org/keywords/lead","display_name":"Lead (geology)","score":0.5865142941474915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5310421586036682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49042412638664246},{"id":"https://openalex.org/keywords/cardiac-arrhythmia","display_name":"Cardiac arrhythmia","score":0.47480833530426025},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4616360366344452},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38072073459625244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35887885093688965},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.13251838088035583},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1277102828025818}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5892822742462158},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.5865142941474915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5310421586036682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49042412638664246},{"id":"https://openalex.org/C2988455589","wikidata":"https://www.wikidata.org/wiki/Q189331","display_name":"Cardiac arrhythmia","level":3,"score":0.47480833530426025},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4616360366344452},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38072073459625244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35887885093688965},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.13251838088035583},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1277102828025818},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/tim.2024.3449956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3449956","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8250733612","display_name":null,"funder_award_id":"2021SHZDZX0102","funder_id":"https://openalex.org/F4320335480","funder_display_name":"Guangzhou Municipal Science and Technology Project"}],"funders":[{"id":"https://openalex.org/F4320335480","display_name":"Guangzhou Municipal Science and Technology Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2004896487","https://openalex.org/W2007178699","https://openalex.org/W2095409369","https://openalex.org/W2108773319","https://openalex.org/W2118305811","https://openalex.org/W2156576661","https://openalex.org/W2338318698","https://openalex.org/W2540590875","https://openalex.org/W2599396866","https://openalex.org/W2605056515","https://openalex.org/W2702116941","https://openalex.org/W2792396409","https://openalex.org/W2805227459","https://openalex.org/W2806806521","https://openalex.org/W2884795774","https://openalex.org/W2886982273","https://openalex.org/W2891342985","https://openalex.org/W2905877654","https://openalex.org/W2910121883","https://openalex.org/W2924118783","https://openalex.org/W2963163009","https://openalex.org/W2964081807","https://openalex.org/W2973489423","https://openalex.org/W2998709384","https://openalex.org/W3009535750","https://openalex.org/W3011574394","https://openalex.org/W3015226328","https://openalex.org/W3021676140","https://openalex.org/W3032941608","https://openalex.org/W3048030988","https://openalex.org/W3088409176","https://openalex.org/W3093086118","https://openalex.org/W3093699748","https://openalex.org/W3099085560","https://openalex.org/W3100321043","https://openalex.org/W3101926760","https://openalex.org/W3111092203","https://openalex.org/W3119243125","https://openalex.org/W3160666973","https://openalex.org/W3199766309","https://openalex.org/W4205381470","https://openalex.org/W4210511145","https://openalex.org/W4221035431","https://openalex.org/W4280603381","https://openalex.org/W4286247627","https://openalex.org/W4292649791","https://openalex.org/W4296397672","https://openalex.org/W4296627555","https://openalex.org/W4297775537","https://openalex.org/W4310423857","https://openalex.org/W4311903808","https://openalex.org/W4315782573","https://openalex.org/W4317651618","https://openalex.org/W4366966565","https://openalex.org/W4376139503","https://openalex.org/W4383744762","https://openalex.org/W4389300266","https://openalex.org/W4390612404","https://openalex.org/W4399875753","https://openalex.org/W4400897535","https://openalex.org/W6637373629","https://openalex.org/W6683128008","https://openalex.org/W6737664043","https://openalex.org/W6741414320"],"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/W4380075502","https://openalex.org/W2807586294","https://openalex.org/W4391114540"],"abstract_inverted_index":{"Although":[0],"significant":[1],"progress":[2],"has":[3],"been":[4],"made":[5],"in":[6,69,90,169],"diagnosing":[7],"arrhythmias,":[8],"current":[9],"deep":[10,62],"neural":[11],"network":[12,46,93,132,237],"(DNN)-based":[13],"methods":[14],"still":[15],"suffer":[16],"from":[17],"misdiagnosis":[18],"and":[19,36,118,166,195,212],"redundant":[20],"parameters.":[21],"One":[22],"reason":[23],"for":[24,65,87,95,244],"this":[25,52,102],"is":[26,54,104,164],"the":[27,37,77,91,120,156,170,175,179,229],"lack":[28],"of":[29,39,43,51,61,101,159,183,200,205,210,216],"high-quality":[30],"clinical":[31,70,96],"12-lead":[32,71,97,181],"electrocardiogram":[33],"(ECG)":[34],"datasets":[35],"absence":[38],"a":[40,57,85,131,143,202,207,213],"systematic":[41],"set":[42],"general":[44],"task-oriented":[45],"lightweight":[47,58,92],"methods.":[48,223],"The":[49,99,224],"objective":[50],"article":[53],"to":[55,105,109],"propose":[56],"optimization":[59],"method":[60,82,103,177,231],"learning":[63],"models":[64],"accurate":[66],"arrhythmia":[67,88],"detection":[68,89,189],"ECG":[72,188],"data.":[73],"We":[74,173],"show":[75],"that":[76,137,228],"proposed":[78,176,230],"optimized":[79],"module":[80,115],"replacement":[81],"can":[83,232],"provide":[84],"strategy":[86],"design":[94,106],"classification.":[98],"key":[100],"compact":[107],"convolution":[108],"replace":[110,147],"standard":[111],"convolutions":[112,150],"based":[113],"on":[114,142],"functional":[116],"equivalence":[117],"identify":[119],"accuracy":[121,160,199],"fractured":[122],"segment":[123],"(AFS).":[124],"To":[125],"achieve":[126,196],"this,":[127],"we":[128],"randomly":[129],"choose":[130],"base":[133],"(the":[134],"initial":[135],"model)":[136],"achieves":[138],"satisfactory":[139],"classification":[140,145,246],"performance":[141,243],"given":[144],"task,":[146],"larger-scale":[148],"parameter":[149,153],"with":[151],"smaller-scale":[152],"convolutions,":[154],"observe":[155],"degenerated":[157],"process":[158],"until":[161],"an":[162,197],"AFS":[163],"found,":[165],"conduct":[167],"tests":[168],"candidate":[171],"models.":[172],"validate":[174],"against":[178],"three-year":[180],"ECGs":[182],"patients":[184],"who":[185],"have":[186],"undergone":[187],"at":[190],"Shanghai":[191],"First":[192],"People\u2019s":[193],"Hospital":[194],"overall":[198],"95.532%,":[201],"precision":[203],"score":[204,209,215],"0.927,":[206],"recall":[208],"0.910,":[211],"specificity":[214],"0.990,":[217],"which":[218],"are":[219],"better":[220],"than":[221],"other":[222],"comparative":[225],"analysis":[226],"shows":[227],"not":[233],"only":[234],"effectively":[235],"reduce":[236],"parameters":[238],"but":[239],"also":[240],"boost":[241],"model":[242],"specific":[245],"tasks.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
