{"id":"https://openalex.org/W3114902075","doi":"https://doi.org/10.1109/ictc49870.2020.9289317","title":"Feature Extraction Model Based on Inception V3 to Distinguish Normal Heart Sound from Systolic Murmur","display_name":"Feature Extraction Model Based on Inception V3 to Distinguish Normal Heart Sound from Systolic Murmur","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3114902075","doi":"https://doi.org/10.1109/ictc49870.2020.9289317","mag":"3114902075"},"language":"en","primary_location":{"id":"doi:10.1109/ictc49870.2020.9289317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","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/A5055127357","display_name":"Jin Hee Bae","orcid":"https://orcid.org/0000-0002-1694-6373"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jinhee Bae","raw_affiliation_strings":["Gachon University, Seongname-si, South Korea"],"affiliations":[{"raw_affiliation_string":"Gachon University, Seongname-si, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100630433","display_name":"Min-Woo Kim","orcid":"https://orcid.org/0000-0001-7610-9772"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minwoo Kim","raw_affiliation_strings":["Gachon University, Seongname-si, South Korea"],"affiliations":[{"raw_affiliation_string":"Gachon University, Seongname-si, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102803771","display_name":"Joon S. Lim","orcid":"https://orcid.org/0000-0002-0018-946X"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joon S. Lim","raw_affiliation_strings":["Gachon University, Seongname-si, South Korea"],"affiliations":[{"raw_affiliation_string":"Gachon University, Seongname-si, South Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055127357"],"corresponding_institution_ids":["https://openalex.org/I12832649"],"apc_list":null,"apc_paid":null,"fwci":0.504,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.71129828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"460","last_page":"463"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12418","display_name":"Respiratory and Cough-Related Research","score":0.97079998254776,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.8826178312301636},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7000442147254944},{"id":"https://openalex.org/keywords/stethoscope","display_name":"Stethoscope","score":0.6353139281272888},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.6343172788619995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6249748468399048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.622583270072937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5904411673545837},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.54680335521698},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5390173196792603},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5297276377677917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5080535411834717},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4542054831981659},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44937965273857117},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4322042763233185},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.42599695920944214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23102223873138428},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1446787714958191},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.1393374502658844},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10619533061981201},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0803714394569397},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.07759132981300354}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8826178312301636},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7000442147254944},{"id":"https://openalex.org/C2779055095","wikidata":"https://www.wikidata.org/wiki/Q162339","display_name":"Stethoscope","level":2,"score":0.6353139281272888},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.6343172788619995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6249748468399048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.622583270072937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5904411673545837},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.54680335521698},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5390173196792603},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5297276377677917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5080535411834717},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4542054831981659},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44937965273857117},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4322042763233185},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.42599695920944214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23102223873138428},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1446787714958191},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.1393374502658844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10619533061981201},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0803714394569397},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.07759132981300354},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","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/ictc49870.2020.9289317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","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":13,"referenced_works":["https://openalex.org/W1554885991","https://openalex.org/W2080157384","https://openalex.org/W2114071902","https://openalex.org/W2183341477","https://openalex.org/W2191779130","https://openalex.org/W2412429158","https://openalex.org/W2592046076","https://openalex.org/W2594894714","https://openalex.org/W2737152053","https://openalex.org/W2962948887","https://openalex.org/W6734269609","https://openalex.org/W6734724335","https://openalex.org/W6741584875"],"related_works":["https://openalex.org/W1972438460","https://openalex.org/W305797682","https://openalex.org/W3028349727","https://openalex.org/W2024262772","https://openalex.org/W2719004936","https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W3134672139","https://openalex.org/W2480617866","https://openalex.org/W4214735274"],"abstract_inverted_index":{"In":[0],"this":[1,121],"study,":[2],"we":[3],"propose":[4],"a":[5,118,162],"model":[6,44],"for":[7,79,104],"classifying":[8],"normal":[9,22],"and":[10,23],"abnormal":[11,17],"sounds":[12,19],"by":[13,138],"extracting":[14],"characteristics":[15,143],"from":[16,81],"heart":[18],"in":[20,120],"which":[21,93],"symbolic":[24],"murmurs":[25],"appear.":[26],"Heart":[27],"sound":[28],"data":[29],"obtained":[30],"through":[31,85],"an":[32,105,113,127],"electronic":[33],"stethoscope":[34],"are":[35],"converted":[36],"into":[37],"mel-spectrogram":[38,51],"images.":[39],"The":[40],"pre-trained":[41],"Inception":[42,60,124],"V3":[43,61,125],"that":[45],"carries":[46],"out":[47],"fine-tuning":[48,58],"uses":[49],"the":[50,82,86,95,98,109,140,149],"image":[52],"as":[53,65,117],"input.":[54],"Convolutional":[55],"layers":[56],"of":[57,97,130],"completed":[59],"models":[62],"were":[63],"used":[64,74,103,112],"feature":[66,87],"extractors.":[67],"A":[68,89],"point-binary":[69],"correlation":[70,99],"analysis":[71],"technique":[72],"was":[73],"to":[75,160],"select":[76],"effective":[77],"features":[78,83],"classification":[80],"extracted":[84],"extractor.":[88],"crystal":[90,146],"coefficient":[91,100,147],"value,":[92,101],"is":[94,102,136,151],"square":[96],"accurate":[106],"comparison":[107],"between":[108],"features.":[110],"We":[111],"artificial":[114],"neural":[115],"network":[116],"classifier":[119],"experiment.":[122],"Fine-tuned":[123],"has":[126],"average":[128],"accuracy":[129,150],"87.7%.":[131],"When":[132],"5-fold":[133],"class":[134],"validation":[135],"advanced":[137],"selecting":[139],"top":[141],"30":[142],"with":[144],"high":[145],"values,":[148],"97.5%.":[152],"These":[153],"results":[154],"can":[155],"greatly":[156],"assist":[157],"physicians":[158],"trying":[159],"detect":[161],"systolic":[163],"murmur.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}