{"id":"https://openalex.org/W4281562993","doi":"https://doi.org/10.1109/icsp54964.2022.9778383","title":"Heart Sound Classification Method based on Ensemble Learning","display_name":"Heart Sound Classification Method based on Ensemble Learning","publication_year":2022,"publication_date":"2022-04-15","ids":{"openalex":"https://openalex.org/W4281562993","doi":"https://doi.org/10.1109/icsp54964.2022.9778383"},"language":"en","primary_location":{"id":"doi:10.1109/icsp54964.2022.9778383","doi":"https://doi.org/10.1109/icsp54964.2022.9778383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsp54964.2022.9778383","pdf_url":null,"source":{"id":"https://openalex.org/S4363607782","display_name":"International Conference on Intelligent Computing and Signal Processing (ICSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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":null,"display_name":"Jin Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Chen","raw_affiliation_strings":["Tiangong University,School of Computer Science and Technology,Tianjin,China","School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tiangong University,School of Computer Science and Technology,Tianjin,China","institution_ids":["https://openalex.org/I198091727"]},{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101880343","display_name":"Xin Dang","orcid":"https://orcid.org/0000-0003-1145-0288","observed_orcids":["https://orcid.org/0000-0003-1145-0288"]},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Dang","raw_affiliation_strings":["Tiangong University,School of Computer Science and Technology,Tianjin,China","School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tiangong University,School of Computer Science and Technology,Tianjin,China","institution_ids":["https://openalex.org/I198091727"]},{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400734","display_name":"Min Li","orcid":"https://orcid.org/0000-0002-3578-2239","observed_orcids":["https://orcid.org/0000-0002-3578-2239"]},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Li","raw_affiliation_strings":["Tiangong University,School of Computer Science and Technology,Tianjin,China","School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tiangong University,School of Computer Science and Technology,Tianjin,China","institution_ids":["https://openalex.org/I198091727"]},{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I198091727"],"apc_list":null,"apc_paid":null,"fwci":5.9473,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.96177474,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"8","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":9.999999747378752e-05,"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/heart-sound-classification","display_name":"heart sound classification","score":1.0},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.9440000057220459},{"id":"https://openalex.org/keywords/stacking","display_name":"stacking","score":0.5699999928474426},{"id":"https://openalex.org/keywords/multi-resolution-features","display_name":"multi-resolution features","score":0.9110000133514404},{"id":"https://openalex.org/keywords/feature-fusion","display_name":"feature fusion","score":0.9860000014305115},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.7919999957084656},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8040000200271606},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9990000128746033},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.9739999771118164},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9399999976158142},{"id":"https://openalex.org/keywords/heart-disease-diagnosis","display_name":"heart disease diagnosis","score":0.3889999985694885}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7017695307731628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7016879320144653},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6788024306297302},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6527947187423706},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6406277418136597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6118472814559937},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5671016573905945},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4999575614929199},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4978947639465332},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4272868037223816},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3443295657634735},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsp54964.2022.9778383","doi":"https://doi.org/10.1109/icsp54964.2022.9778383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsp54964.2022.9778383","pdf_url":null,"source":{"id":"https://openalex.org/S4363607782","display_name":"International Conference on Intelligent Computing and Signal Processing (ICSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8048999905586243,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2043999892","https://openalex.org/W2082567546","https://openalex.org/W2147256684","https://openalex.org/W2301158262","https://openalex.org/W2557139718","https://openalex.org/W2593628220","https://openalex.org/W2594557222","https://openalex.org/W3044259016"],"related_works":["https://openalex.org/W7160710621","https://openalex.org/W3014826487","https://openalex.org/W2808011919","https://openalex.org/W4417425710","https://openalex.org/W2593582951","https://openalex.org/W4411463798","https://openalex.org/W4414152069","https://openalex.org/W4399358897","https://openalex.org/W4386108447","https://openalex.org/W4404664445"],"abstract_inverted_index":{"Heart":[0],"sound":[1,24,65,117],"classification":[2,8],"aims":[3],"to":[4,58,91,102],"explore":[5],"a":[6,31,112,141],"reasonable":[7],"method":[9,52,114],"of":[10,19,44,62,121],"pathological":[11],"events.":[12],"The":[13,145],"single-scale":[14],"character":[15],"only":[16],"shows":[17],"part":[18],"the":[20,38,60,72,85,130,134,138,153,162],"information":[21],"on":[22],"heart":[23,64,116],"signal.":[25],"Different":[26],"machine":[27],"learning":[28,51,155],"methods":[29],"have":[30],"difference":[32],"in":[33],"performances.":[34],"This":[35],"paper":[36,110],"studies":[37],"performance":[39,146],"differences":[40],"between":[41],"multi-resolution":[42],"features":[43,55,104],"different":[45],"classifiers,":[46],"and":[47,56,77,98,127,137,161],"uses":[48,111],"an":[49,149],"ensemble":[50,154],"that":[53],"combines":[54],"classifiers":[57,132],"improve":[59],"accuracy":[61],"automatic":[63],"classification.":[66,118],"In":[67],"this":[68,109],"work,":[69],"we":[70],"extract":[71],"time":[73],"domain,":[74,76],"frequency":[75],"statistical":[78],"characteristics":[79],"as":[80,133],"feature":[81,100],"vectors,":[82],"then":[83],"use":[84],"Principal":[86],"Component":[87],"Analysis":[88],"(PCA)":[89],"technology":[90],"reduce":[92],"dimensions":[93],"for":[94,115],"avoiding":[95],"redundant":[96],"features,":[97],"apply":[99],"fusion":[101],"splice":[103],"from":[105],"multiple":[106],"fields.":[107],"Finally,":[108],"stacking":[113],"It":[119],"consists":[120],"two":[122],"layers,":[123],"SVM,":[124],"Random":[125],"Forest,":[126],"KNN":[128],"are":[129,165],"primary":[131],"first":[135],"layer,":[136],"secondary":[139],"is":[140],"logistic":[142],"regression":[143],"model.":[144],"evaluation":[147],"has":[148],"evident":[150],"improvement":[151],"with":[152],"method,":[156],"its":[157],"accuracy,":[158],"sensitivity,":[159],"specificity,":[160],"overall":[163],"score":[164],"97.28%,":[166],"98.45%,":[167],"96.12%,":[168],"97.285%":[169],"respectively.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2022-05-27T00:00:00"}