{"id":"https://openalex.org/W2947527789","doi":"https://doi.org/10.1109/access.2019.2919485","title":"Early and Remote Detection of Possible Heartbeat Problems With Convolutional Neural Networks and Multipart Interactive Training","display_name":"Early and Remote Detection of Possible Heartbeat Problems With Convolutional Neural Networks and Multipart Interactive Training","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2947527789","doi":"https://doi.org/10.1109/access.2019.2919485","mag":"2947527789"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2919485","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919485","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723396.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723396.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030149703","display_name":"Krzysztof Wo\u0142k","orcid":"https://orcid.org/0000-0001-5030-334X"},"institutions":[{"id":"https://openalex.org/I3017851245","display_name":"Polish-Japanese Academy of Information Technology","ror":"https://ror.org/01v542j61","country_code":"PL","type":"education","lineage":["https://openalex.org/I3017851245"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Wolk","raw_affiliation_strings":["Polish-Japanese Academy of Information Technology, Warsaw, Poland"],"raw_orcid":"https://orcid.org/0000-0001-5030-334X","affiliations":[{"raw_affiliation_string":"Polish-Japanese Academy of Information Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I3017851245"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009169567","display_name":"Agnieszka Wo\u0142k","orcid":"https://orcid.org/0000-0002-9667-2068"},"institutions":[{"id":"https://openalex.org/I3017851245","display_name":"Polish-Japanese Academy of Information Technology","ror":"https://ror.org/01v542j61","country_code":"PL","type":"education","lineage":["https://openalex.org/I3017851245"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Agnieszka Wolk","raw_affiliation_strings":["Polish-Japanese Academy of Information Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polish-Japanese Academy of Information Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I3017851245"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3017851245"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4615,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.83777208,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"145921","last_page":"145927"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":1.0,"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":1.0,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9991999864578247,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/computer-science","display_name":"Computer science","score":0.8685770630836487},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7379285097122192},{"id":"https://openalex.org/keywords/heartbeat","display_name":"Heartbeat","score":0.676175057888031},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.6525740027427673},{"id":"https://openalex.org/keywords/stethoscope","display_name":"Stethoscope","score":0.6510334014892578},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5657926797866821},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5499701499938965},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5026309490203857},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4938293397426605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.430440753698349},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4043850302696228},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3468363881111145},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.12554055452346802}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8685770630836487},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7379285097122192},{"id":"https://openalex.org/C13852961","wikidata":"https://www.wikidata.org/wiki/Q17021880","display_name":"Heartbeat","level":2,"score":0.676175057888031},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.6525740027427673},{"id":"https://openalex.org/C2779055095","wikidata":"https://www.wikidata.org/wiki/Q162339","display_name":"Stethoscope","level":2,"score":0.6510334014892578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5657926797866821},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5499701499938965},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5026309490203857},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4938293397426605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.430440753698349},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4043850302696228},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3468363881111145},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.12554055452346802},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2919485","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919485","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723396.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8222d88c7c35496ebb825171e8ba6bb0","is_oa":true,"landing_page_url":"https://doaj.org/article/8222d88c7c35496ebb825171e8ba6bb0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 145921-145927 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2919485","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919485","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723396.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2947527789.pdf","grobid_xml":"https://content.openalex.org/works/W2947527789.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1978142137","https://openalex.org/W2015332508","https://openalex.org/W2027215587","https://openalex.org/W2061880411","https://openalex.org/W2064493351","https://openalex.org/W2073294224","https://openalex.org/W2093231248","https://openalex.org/W2104330778","https://openalex.org/W2104614052","https://openalex.org/W2107216691","https://openalex.org/W2115340664","https://openalex.org/W2117624000","https://openalex.org/W2124785086","https://openalex.org/W2140920882","https://openalex.org/W2251133041","https://openalex.org/W2263065115","https://openalex.org/W2540718148","https://openalex.org/W2605327945","https://openalex.org/W2613181244","https://openalex.org/W2621205740","https://openalex.org/W2731010577","https://openalex.org/W2748902594","https://openalex.org/W2761639295","https://openalex.org/W2766619178","https://openalex.org/W2789714263","https://openalex.org/W2795328221","https://openalex.org/W2799601587","https://openalex.org/W2895271304","https://openalex.org/W2904355766","https://openalex.org/W2911420178","https://openalex.org/W2962750725","https://openalex.org/W2962948887","https://openalex.org/W2963478701","https://openalex.org/W4241637638","https://openalex.org/W6631190155","https://openalex.org/W6740609221","https://openalex.org/W6741584875"],"related_works":["https://openalex.org/W3178141655","https://openalex.org/W4312887852","https://openalex.org/W2981877337","https://openalex.org/W3203938600","https://openalex.org/W4286910063","https://openalex.org/W2163707935","https://openalex.org/W83146503","https://openalex.org/W202723009","https://openalex.org/W2145955964","https://openalex.org/W2188612292"],"abstract_inverted_index":{"In":[0],"this":[1,89],"study,":[2],"the":[3,20,36,45,58,61,67,70,120,128,136,185],"convolutional":[4],"neural":[5],"network":[6],"(CNN)":[7],"and":[8,44,64,81,124,141,174],"multipart":[9],"interactive":[10,139],"training":[11,140],"were":[12,47,55,83,133],"used":[13,65,92],"to":[14,95,104,113,156,184],"create":[15],"a":[16,41,115,161,167],"state-of-the-art":[17],"classifier":[18],"for":[19,171],"early":[21],"detection":[22],"of":[23,33,57,72,117],"cardiac":[24],"pathologies.":[25],"The":[26,131],"classification":[27],"was":[28,38,91,111],"performed":[29],"using":[30,40,85,135,160],"three":[31],"sets":[32],"data":[34,54,183],"samples;":[35],"first":[37],"recorded":[39,48],"digital":[42],"stethoscope":[43],"others":[46],"with":[49,119,127],"mobile":[50],"smart":[51],"devices.":[52],"These":[53],"part":[56],"competition":[59],"on":[60,66],"Kaggle":[62],"platform":[63],"CNN":[68],"in":[69,78,148],"form":[71],"audio":[73],"samples":[74],"as":[75,77],"well":[76],"spectrogram":[79],"format,":[80],"experiments":[82,132],"conducted":[84,134],"both":[86],"methods.":[87],"Moreover,":[88],"method":[90],"not":[93],"only":[94],"distinguish":[96],"healthy":[97],"from":[98],"unhealthy":[99],"heart":[100],"rhythm":[101],"but":[102],"also":[103,165],"attempt":[105],"reaching":[106],"some":[107],"initial":[108],"diagnosis.":[109],"It":[110,164],"possible":[112,179],"identify":[114],"set":[116],"problems":[118],"dataset,":[121],"make":[122],"corrections,":[123],"share":[125],"them":[126],"scientific":[129],"community.":[130],"so-called":[137],"multi-part":[138],"an":[142],"additional":[143],"ResNet":[144],"pre-trained":[145],"network,":[146],"resulting":[147],"more":[149,182],"than":[150],"93%":[151],"precision.":[152],"This":[153],"allows":[154],"anyone":[155],"undertake":[157],"prophylactical":[158],"diagnosis":[159],"smartphone":[162],"alone.":[163],"has":[166],"great":[168],"educational":[169],"potential":[170],"young":[172],"doctors":[173],"students.":[175],"Greater":[176],"improvement":[177],"is":[178],"by":[180],"supplying":[181],"described":[186],"method.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
