{"id":"https://openalex.org/W3173545181","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459909","title":"A Deep Convolutional Neural Network Classification of Heart Sounds using Fractional Fourier Transform","display_name":"A Deep Convolutional Neural Network Classification of Heart Sounds using Fractional Fourier Transform","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3173545181","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459909","mag":"3173545181"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc50364.2021.9459909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5112489092","display_name":"Ebrahim A. Nehary","orcid":null},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"E.A. Nehary","raw_affiliation_strings":["Systems and Computer Engineering, Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"Systems and Computer Engineering, Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085417561","display_name":"Zaid Abduh","orcid":null},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Zaid Abduh","raw_affiliation_strings":["Biomedical Engineering and Systems, Cairo University, Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering and Systems, Cairo University, Cairo, Egypt","institution_ids":["https://openalex.org/I145487455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012603099","display_name":"Sreeraman Rajan","orcid":"https://orcid.org/0000-0003-0153-6723"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sreeraman Rajan","raw_affiliation_strings":["Systems and Computer Engineering, Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"Systems and Computer Engineering, Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112489092"],"corresponding_institution_ids":["https://openalex.org/I67031392"],"apc_list":null,"apc_paid":null,"fwci":0.8806,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.74941772,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T12537","display_name":"Flow Measurement and Analysis","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9800999760627747,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.719363808631897},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7107431888580322},{"id":"https://openalex.org/keywords/phonocardiogram","display_name":"Phonocardiogram","score":0.6847410202026367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6629303097724915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.600680947303772},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.583953320980072},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5667949318885803},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5603729486465454},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5184842944145203},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49527111649513245},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.46956419944763184},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45864468812942505},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.44843265414237976},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.4409205913543701},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.4125276207923889},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3629661202430725},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28971579670906067},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.20927393436431885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15210723876953125},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.07918646931648254}],"concepts":[{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.719363808631897},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7107431888580322},{"id":"https://openalex.org/C159693508","wikidata":"https://www.wikidata.org/wiki/Q3301075","display_name":"Phonocardiogram","level":2,"score":0.6847410202026367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6629303097724915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.600680947303772},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.583953320980072},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5667949318885803},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5603729486465454},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5184842944145203},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49527111649513245},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.46956419944763184},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45864468812942505},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.44843265414237976},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.4409205913543701},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.4125276207923889},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3629661202430725},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28971579670906067},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.20927393436431885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15210723876953125},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.07918646931648254},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc50364.2021.9459909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1908126967","https://openalex.org/W2006442389","https://openalex.org/W2080157384","https://openalex.org/W2095705004","https://openalex.org/W2098654070","https://openalex.org/W2110063971","https://openalex.org/W2128653836","https://openalex.org/W2136106070","https://openalex.org/W2155935604","https://openalex.org/W2301158262","https://openalex.org/W2439311624","https://openalex.org/W2557139718","https://openalex.org/W2591957616","https://openalex.org/W2592074136","https://openalex.org/W2593628220","https://openalex.org/W2622526092","https://openalex.org/W2623291382","https://openalex.org/W2891328462","https://openalex.org/W2906028509","https://openalex.org/W2944090083","https://openalex.org/W2963652317","https://openalex.org/W2964121744","https://openalex.org/W2993118585","https://openalex.org/W3048138536","https://openalex.org/W3145320818","https://openalex.org/W6674330103","https://openalex.org/W6698041239","https://openalex.org/W6734306856","https://openalex.org/W6734430412"],"related_works":["https://openalex.org/W2103138788","https://openalex.org/W2143985734","https://openalex.org/W2065632335","https://openalex.org/W2353397954","https://openalex.org/W2254915314","https://openalex.org/W3025065882","https://openalex.org/W2360207186","https://openalex.org/W19668000","https://openalex.org/W1630261230","https://openalex.org/W1967434260"],"abstract_inverted_index":{"A":[0],"computer-aided":[1],"auscultation":[2],"system":[3,21,65,132],"can":[4],"help":[5],"in":[6,78],"the":[7,44,60,91,94,138],"initial":[8],"diagnosis":[9],"of":[10,62,93,120],"heart":[11],"diseases.":[12],"In":[13],"this":[14],"work,":[15],"we":[16],"propose":[17],"a":[18,33,67,112],"binary":[19,142],"classification":[20,145],"that":[22,72],"uses":[23],"fractional":[24,52,103],"Fourier":[25],"transform":[26],"based":[27],"Mel-frequency":[28],"spectral":[29],"coefficients":[30],"(FrFT-MFSC)":[31],"and":[32,83,115,118,122],"1D":[34],"deep":[35],"convolutional":[36],"neural":[37],"network.":[38],"FrFt-MFSC":[39],"is":[40,105,134],"used":[41,88],"to":[42,89,136],"convert":[43],"phonocardiogram":[45],"(PCG)":[46],"into":[47],"heat":[48],"maps":[49],"using":[50,66,101,126],"four":[51],"orders":[53,104],"(0.9,":[54],"0.95,":[55],"1.0,":[56],"1.10).":[57],"We":[58],"verify":[59],"performance":[61,92,97,114,133],"our":[63],"proposed":[64,131],"publicly":[68],"available":[69],"data":[70,128],"set":[71],"was":[73],"provided":[74],"by":[75],"2016":[76],"Physionet/Computing":[77],"Cardiology":[79],"Challenge.":[80],"Ten-fold":[81],"cross-validation":[82,110],"holdout":[84],"test":[85],"methods":[86],"are":[87],"evaluate":[90],"system.":[95],"Classifier":[96],"for":[98],"various":[99],"features":[100],"different":[102],"also":[106],"studied.":[107],"The":[108,130],"10-fold":[109],"provides":[111],"good":[113],"balanced":[116],"specificity":[117],"sensitivity":[119],"0.97":[121],"0.95":[123],"respectively":[124],"despite":[125],"imbalance":[127],"set.":[129],"superior":[135],"all":[137],"current":[139],"state-of-the":[140],"art":[141],"human":[143],"PCG":[144],"systems.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
