{"id":"https://openalex.org/W7126036650","doi":"https://doi.org/10.1109/bibm66473.2025.11356632","title":"DF-MLSL: An Effective Distillation Framework for Multi-Label Single-Lead ECG Classification","display_name":"DF-MLSL: An Effective Distillation Framework for Multi-Label Single-Lead ECG Classification","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126036650","doi":"https://doi.org/10.1109/bibm66473.2025.11356632"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5102019201","display_name":"Yupeng Qiang","orcid":"https://orcid.org/0009-0003-3908-4328"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yupeng Qiang","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123670035","display_name":"Xunde Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xunde Dong","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076298546","display_name":"Xiuling Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuling Liu","raw_affiliation_strings":["Hebei University,Key Laboratory of Digital Medical Engineering of Hebei Province,Baoding,China"],"affiliations":[{"raw_affiliation_string":"Hebei University,Key Laboratory of Digital Medical Engineering of Hebei Province,Baoding,China","institution_ids":["https://openalex.org/I43337087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124197217","display_name":"Chen Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Xu","raw_affiliation_strings":["Ministry of Education Beijing Institute of Technology,Key Laboratory of Brain Health Intelligent Evaluation and Intervention,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education Beijing Institute of Technology,Key Laboratory of Brain Health Intelligent Evaluation and Intervention,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124237757","display_name":"Fei Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Hu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060334067","display_name":"Rongjia Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongjia Wang","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102019201"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70651191,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4030","last_page":"4035"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.8616999983787537,"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":0.8616999983787537,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.05869999900460243,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.008299999870359898,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7804999947547913},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5461000204086304},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5306000113487244},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.506600022315979},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4180000126361847},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3828999996185303},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.3797999918460846}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7804999947547913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652400016784668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6294999718666077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5482000112533569},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5306000113487244},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.506600022315979},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4180000126361847},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3808000087738037},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C154030694","wikidata":"https://www.wikidata.org/wiki/Q1436074","display_name":"Fractionating column","level":3,"score":0.3666999936103821},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.362199991941452},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3116999864578247}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4913123548030853,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G6039320489","display_name":null,"funder_award_id":"62450100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2407386500","https://openalex.org/W2551393996","https://openalex.org/W2902644322","https://openalex.org/W2972810968","https://openalex.org/W3084949122","https://openalex.org/W3119163262","https://openalex.org/W3177196641","https://openalex.org/W3193014534","https://openalex.org/W4206909988","https://openalex.org/W4226426325","https://openalex.org/W4285605332","https://openalex.org/W4292856638","https://openalex.org/W4293382753","https://openalex.org/W4318200329","https://openalex.org/W4366306875","https://openalex.org/W4377704664","https://openalex.org/W4386866128"],"related_works":[],"abstract_inverted_index":{"Automated":[0],"ECG":[1,14,69,179],"analysis":[2],"researches":[3],"can":[4],"be":[5],"categorized":[6],"into":[7],"single-lead":[8,32,51,68,177],"and":[9,96,98],"multi-lead":[10,13],"approaches.":[11],"While":[12],"diagnostic":[15],"models":[16],"have":[17],"achieved":[18],"expert-level":[19],"performance":[20,172],"using":[21],"deep":[22],"learning,":[23],"their":[24,35],"data":[25],"acquisition":[26],"is":[27,115,122],"less":[28],"convenient":[29],"compared":[30],"to":[31,152,163],"ECGs,":[33],"limiting":[34],"application.":[36],"Additionally,":[37],"traditional":[38],"knowledge":[39,62,148],"distillation":[40,63],"techniques":[41],"face":[42],"challenges":[43],"in":[44,169],"handling":[45],"multi-label":[46,50,67,106,161,178],"data.":[47,107],"To":[48],"enhance":[49],"ECG-based":[52],"cardiac":[53],"disease":[54],"diagnosis,":[55],"this":[56,109],"paper":[57],"presents":[58],"DF-MLSL,":[59],"an":[60],"efficient":[61],"frame-work":[64],"designed":[65,104],"for":[66,92,105,176],"classification.":[70],"The":[71],"framework":[72],"consists":[73],"of":[74,146,167,173],"three":[75,132,160],"main":[76],"losses:":[77],"Last":[78],"Layer":[79],"Features":[80],"Distillation":[81,89,101],"(LLFD)":[82],"based":[83,124],"on":[84,125,159],"feature":[85],"matching,":[86],"Sigmoid":[87],"Regression":[88],"(SRD)":[90],"loss":[91,103,128],"decoupled":[93],"representation":[94],"learning":[95],"classification,":[97],"Multi-Label":[99],"Logits":[100],"(MLLD)":[102],"In":[108],"framework,":[110],"the":[111,118,144,150,153,165,171,174],"teacher":[112],"network":[113,120],"(T-net)":[114],"pretrained.":[116],"Subsequently,":[117],"student":[119],"(S-net)":[121],"trained":[123],"a":[126],"composite":[127],"function":[129],"that":[130],"incorporates":[131],"specialized":[133],"losses":[134],"along":[135],"with":[136],"standard":[137],"binary":[138],"cross-entropy":[139],"(BCE)":[140],"loss.":[141],"This":[142],"enables":[143],"transfer":[145],"latent":[147],"from":[149],"T-net":[151],"S-net.":[154],"Experimental":[155],"evaluations":[156],"were":[157],"conducted":[158],"datasets":[162],"demonstrate":[164],"effectiveness":[166],"DF-MLSL":[168],"enhancing":[170],"S-net":[175],"classification":[180],"tasks.":[181]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}
