{"id":"https://openalex.org/W3106654658","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263559","title":"Automatic Classification of 12-lead ECG Based on Model Fusion","display_name":"Automatic Classification of 12-lead ECG Based on Model Fusion","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3106654658","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263559","mag":"3106654658"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei51763.2020.9263559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th 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/A5075030851","display_name":"Xiaohong Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I161346416","display_name":"Jimei University","ror":"https://ror.org/03hknyb50","country_code":"CN","type":"education","lineage":["https://openalex.org/I161346416"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohong Ye","raw_affiliation_strings":["Jimei University,Chengyi University College,Xiamen,China","Chengyi University College, Jimei University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Jimei University,Chengyi University College,Xiamen,China","institution_ids":["https://openalex.org/I161346416"]},{"raw_affiliation_string":"Chengyi University College, Jimei University, Xiamen, China","institution_ids":["https://openalex.org/I161346416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111935848","display_name":"Qiang L\u00fc","orcid":null},"institutions":[{"id":"https://openalex.org/I161346416","display_name":"Jimei University","ror":"https://ror.org/03hknyb50","country_code":"CN","type":"education","lineage":["https://openalex.org/I161346416"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Lu","raw_affiliation_strings":["Jimei University,School of Science,Xiamen,China","School of Science, Jimei University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Jimei University,School of Science,Xiamen,China","institution_ids":["https://openalex.org/I161346416"]},{"raw_affiliation_string":"School of Science, Jimei University, Xiamen, China","institution_ids":["https://openalex.org/I161346416"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075030851"],"corresponding_institution_ids":["https://openalex.org/I161346416"],"apc_list":null,"apc_paid":null,"fwci":0.5975,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71950066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"733","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9609000086784363,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9592000246047974,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7125034332275391},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.599128782749176},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5889537930488586},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5763079524040222},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5050879120826721},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.49374303221702576},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4850679934024811},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4671693742275238},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4469241797924042},{"id":"https://openalex.org/keywords/electrocardiography","display_name":"Electrocardiography","score":0.4258442223072052},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.14034360647201538},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11358651518821716},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10511037707328796},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.08225208520889282}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7125034332275391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.599128782749176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5889537930488586},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5763079524040222},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5050879120826721},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.49374303221702576},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4850679934024811},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4671693742275238},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4469241797924042},{"id":"https://openalex.org/C2780040984","wikidata":"https://www.wikidata.org/wiki/Q79785","display_name":"Electrocardiography","level":2,"score":0.4258442223072052},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.14034360647201538},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11358651518821716},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10511037707328796},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.08225208520889282},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei51763.2020.9263559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th 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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W197865394","https://openalex.org/W1799366690","https://openalex.org/W1836465849","https://openalex.org/W1999965501","https://openalex.org/W2009977195","https://openalex.org/W2028276885","https://openalex.org/W2043820901","https://openalex.org/W2063923412","https://openalex.org/W2064675550","https://openalex.org/W2076360516","https://openalex.org/W2104518905","https://openalex.org/W2130769894","https://openalex.org/W2141125852","https://openalex.org/W2143612262","https://openalex.org/W2156458269","https://openalex.org/W2289846183","https://openalex.org/W2295598076","https://openalex.org/W2743850381","https://openalex.org/W2747849569","https://openalex.org/W2767619996","https://openalex.org/W2777186991","https://openalex.org/W2806806521","https://openalex.org/W2888456553","https://openalex.org/W2898941944","https://openalex.org/W2899736836","https://openalex.org/W2902644322","https://openalex.org/W2909762442","https://openalex.org/W2944090748","https://openalex.org/W2947810057","https://openalex.org/W2949117887","https://openalex.org/W2953193031","https://openalex.org/W2965307660","https://openalex.org/W2995942064","https://openalex.org/W3102476541"],"related_works":["https://openalex.org/W3093612317","https://openalex.org/W3157227329","https://openalex.org/W2010832783","https://openalex.org/W2003125512","https://openalex.org/W2175746458","https://openalex.org/W2732542196","https://openalex.org/W2760085659","https://openalex.org/W2883200793","https://openalex.org/W2738221750","https://openalex.org/W3116403876"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,14,60,65,92,116,121,144],"growing":[3],"demand":[4],"for":[5,127,143],"automatic":[6,19],"analysis":[7],"of":[8,21,77,86,95,101,106,112,120,147],"standard":[9],"12-lead":[10,22,61,135],"electrocardiogram":[11],"(ECG)":[12],"in":[13,73],"medical":[15],"diagnosis":[16,146],"process,":[17],"an":[18,97],"classification":[20,66],"ECG":[23,78],"based":[24,124],"on":[25,125],"model":[26,81,123],"fusion":[27,80,122],"is":[28,56],"proposed.":[29],"The":[30,68,137],"algorithm":[31],"extracts":[32,42],"local":[33],"features":[34,44],"by":[35,45],"Convolutional":[36],"Neural":[37],"Networks":[38],"(CNN),":[39],"and":[40,108,118],"then":[41],"temporal":[43],"Bi-directional":[46],"Long":[47],"Short-term":[48],"Memory":[49],"(BiLSTM).":[50],"Finally,":[51],"eXtreme":[52],"Gradient":[53],"Boosting":[54],"(XGBoost)":[55],"used":[57],"to":[58,63,134],"fuse":[59],"models":[62],"get":[64],"results.":[67],"experiment":[69],"result":[70],"shows":[71],"that,":[72],"classifying":[74],"9":[75,129],"types":[76],"singles,":[79],"achieved":[82],"a":[83,88,103,109],"mean":[84,104,110],"accuracy":[85],"0.964,":[87],"micro-average":[89],"area":[90],"under":[91],"curve":[93],"(AUC)":[94],"0.908,":[96],"average":[98],"F1":[99],"score":[100],"0.812,":[102],"precision":[105],"0.836,":[107],"recall":[111],"0.788.":[113],"We":[114],"demonstrated":[115],"feasibility":[117],"effectiveness":[119],"XGBoost":[126],"interpreting":[128],"common":[130],"heart":[131],"rhythms":[132],"according":[133],"ECG.":[136],"findings":[138],"may":[139],"have":[140],"clinical":[141],"relevance":[142],"early":[145],"cardiac-rhythm":[148],"disorders.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-01-11T23:08:45.486102","created_date":"2025-10-10T00:00:00"}