{"id":"https://openalex.org/W3082512216","doi":"https://doi.org/10.1109/embc44109.2020.9176544","title":"Rheumatic Heart Disease Detection Using Deep Learning from Spectro-Temporal Representation of Un-segmented Heart Sounds","display_name":"Rheumatic Heart Disease Detection Using Deep Learning from Spectro-Temporal Representation of Un-segmented Heart Sounds","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3082512216","doi":"https://doi.org/10.1109/embc44109.2020.9176544","mag":"3082512216","pmid":"https://pubmed.ncbi.nlm.nih.gov/33017956"},"language":"en","primary_location":{"id":"doi:10.1109/embc44109.2020.9176544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9176544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5014137366","display_name":"Melkamu Hunegnaw Asmare","orcid":"https://orcid.org/0000-0003-0990-3348"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Melkamu Hunegnaw Asmare","raw_affiliation_strings":["eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051022448","display_name":"Frehiwot Woldehanna","orcid":null},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Frehiwot Woldehanna","raw_affiliation_strings":["eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088365375","display_name":"Luc Janssens","orcid":"https://orcid.org/0000-0001-6827-9325"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Luc Janssens","raw_affiliation_strings":["eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016823997","display_name":"Bart Vanrumste","orcid":"https://orcid.org/0000-0002-9409-935X"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Bart Vanrumste","raw_affiliation_strings":["eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"eMedia research, Campus GroepT, KU Leuven, Leuven, Belgium and STADIUS, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2020","issue":null,"first_page":"168","last_page":"171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T11153","display_name":"Streptococcal Infections and Treatments","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"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":0.9595999717712402,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/phonocardiogram","display_name":"Phonocardiogram","score":0.8193556070327759},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6505234241485596},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6278272867202759},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6204596757888794},{"id":"https://openalex.org/keywords/auscultation","display_name":"Auscultation","score":0.5858505964279175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5841794013977051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5419114828109741},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5258139967918396},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5038711428642273},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5018725395202637},{"id":"https://openalex.org/keywords/stethoscope","display_name":"Stethoscope","score":0.4892144203186035},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45466533303260803},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.426258385181427},{"id":"https://openalex.org/keywords/heart-disease","display_name":"Heart disease","score":0.42601656913757324},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.2365606427192688},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2177501618862152}],"concepts":[{"id":"https://openalex.org/C159693508","wikidata":"https://www.wikidata.org/wiki/Q3301075","display_name":"Phonocardiogram","level":2,"score":0.8193556070327759},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6505234241485596},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6278272867202759},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6204596757888794},{"id":"https://openalex.org/C2777324038","wikidata":"https://www.wikidata.org/wiki/Q779054","display_name":"Auscultation","level":2,"score":0.5858505964279175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5841794013977051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5419114828109741},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5258139967918396},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5038711428642273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5018725395202637},{"id":"https://openalex.org/C2779055095","wikidata":"https://www.wikidata.org/wiki/Q162339","display_name":"Stethoscope","level":2,"score":0.4892144203186035},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45466533303260803},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.426258385181427},{"id":"https://openalex.org/C2780074459","wikidata":"https://www.wikidata.org/wiki/Q389735","display_name":"Heart disease","level":2,"score":0.42601656913757324},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.2365606427192688},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2177501618862152},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006347","descriptor_name":"Heart Sounds","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006347","descriptor_name":"Heart Sounds","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006347","descriptor_name":"Heart Sounds","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012214","descriptor_name":"Rheumatic Heart Disease","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D012214","descriptor_name":"Rheumatic Heart Disease","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D012214","descriptor_name":"Rheumatic Heart Disease","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc44109.2020.9176544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9176544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:33017956","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33017956","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2511730936","https://openalex.org/W2593628220","https://openalex.org/W2623291382","https://openalex.org/W2709581992","https://openalex.org/W2731010577","https://openalex.org/W2746455801","https://openalex.org/W2751841560","https://openalex.org/W2808937140","https://openalex.org/W2809598685","https://openalex.org/W2937047963","https://openalex.org/W2963446712","https://openalex.org/W6734306856","https://openalex.org/W6740609221"],"related_works":["https://openalex.org/W2596349967","https://openalex.org/W4294762469","https://openalex.org/W4380301583","https://openalex.org/W2077460349","https://openalex.org/W2497721607","https://openalex.org/W2083400547","https://openalex.org/W2952454465","https://openalex.org/W4312229671","https://openalex.org/W2031186051","https://openalex.org/W4372271870"],"abstract_inverted_index":{"Rheumatic":[0],"Heart":[1],"Disease":[2],"(RHD)":[3],"is":[4,54,71,90,118,148,171,205],"an":[5,75,121,199,225],"autoimmune":[6],"response":[7],"to":[8,41,73,136],"a":[9,43,46,63,132,149,167,191],"bacterial":[10],"attack":[11],"which":[12,35,154],"deteriorates":[13],"the":[14,18,24,27,32,49,81,96,99,101,115,139,145,156,165,183],"normal":[15,28,85],"functioning":[16],"of":[17,52,98,114,123,185,228],"heart":[19,33,82,107,201],"valves.":[20],"The":[21,88,112,173,222],"damage":[22],"on":[23,92],"valves":[25],"affects":[26],"blood":[29],"flow":[30],"inside":[31],"chambers":[34],"can":[36],"be":[37],"recorded":[38,206],"and":[39,58,78,86,103,105,126,163,233,235],"listened":[40],"via":[42],"stethoscope":[44],"as":[45,84,120],"phonocardiogram.":[47],"However,":[48],"manual":[50],"method":[51],"auscultation":[53,77],"difficult,":[55],"time":[56,162],"consuming":[57],"subjective.":[59],"In":[60],"this":[61,196],"study,":[62,198],"convolutional":[64,177,187],"neural":[65,188],"network":[66,117,174,189],"based":[67],"deep":[68,186],"learning":[69],"algorithm":[70],"used":[72],"perform":[74],"automatic":[76],"it":[79],"classifies":[80],"sound":[83,202],"rheumatic.":[87],"classification":[89],"done":[91],"un-segmented":[93],"data":[94,203],"where":[95],"extraction":[97],"first,":[100],"second":[102],"systolic":[104],"diastolic":[106],"sounds":[108],"are":[109,142,218],"not":[110],"required.":[111],"architecture":[113],"CNN":[116],"formed":[119],"array":[122],"layers.":[124,178],"Convolutional":[125],"batch":[127],"normalization":[128],"layers":[129],"followed":[130],"by":[131],"max":[133,151],"pooling":[134,152],"layer":[135,153,170],"down":[137],"sample":[138],"feature":[140,158],"maps":[141],"used.":[143],"At":[144],"end":[146,166],"there":[147],"final":[150],"pools":[155],"input":[157],"map":[159],"globally":[160],"over":[161],"at":[164],"fully":[168],"connected":[169],"included.":[172],"has":[175,224],"five":[176],"This":[179],"current":[180,197],"work":[181],"illustrates":[182],"use":[184],"using":[190],"Mel":[192],"Spectro-temporal":[193],"representation.":[194],"For":[195],"RHD":[200,220],"set":[204],"from":[207,212],"one":[208,214],"hundred":[209,215],"seventy":[210],"subjects":[211],"whom":[213],"twenty":[216],"four":[217],"confirmed":[219],"patients.":[221],"system":[223],"overall":[226],"accuracy":[227],"96.1%":[229],"with":[230],"94.0%":[231],"sensitivity":[232],"98.1%":[234],"specificity.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}