{"id":"https://openalex.org/W3197632104","doi":"https://doi.org/10.3390/e23091121","title":"ECG Signal Classification Using Deep Learning Techniques Based on the PTB-XL Dataset","display_name":"ECG Signal Classification Using Deep Learning Techniques Based on the PTB-XL Dataset","publication_year":2021,"publication_date":"2021-08-28","ids":{"openalex":"https://openalex.org/W3197632104","doi":"https://doi.org/10.3390/e23091121","mag":"3197632104","pmid":"https://pubmed.ncbi.nlm.nih.gov/34573746"},"language":"en","primary_location":{"id":"doi:10.3390/e23091121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091121","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1121/pdf?version=1630636250","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/9/1121/pdf?version=1630636250","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084203907","display_name":"Sandra \u015amigiel","orcid":"https://orcid.org/0000-0003-2459-5494"},"institutions":[{"id":"https://openalex.org/I1300393620","display_name":"Bydgoszcz University of Science and Technology","ror":"https://ror.org/049eq0c58","country_code":"PL","type":"education","lineage":["https://openalex.org/I1300393620"]},{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Sandra \u015amigiel","raw_affiliation_strings":["Faculty of Mechanical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland"],"raw_orcid":"https://orcid.org/0000-0003-2459-5494","affiliations":[{"raw_affiliation_string":"Faculty of Mechanical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland","institution_ids":["https://openalex.org/I686019","https://openalex.org/I1300393620"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008068058","display_name":"Krzysztof Pa\u0142czy\u0144ski","orcid":"https://orcid.org/0000-0003-3989-3400"},"institutions":[{"id":"https://openalex.org/I1300393620","display_name":"Bydgoszcz University of Science and Technology","ror":"https://ror.org/049eq0c58","country_code":"PL","type":"education","lineage":["https://openalex.org/I1300393620"]},{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Pa\u0142czy\u0144ski","raw_affiliation_strings":["Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland"],"raw_orcid":"https://orcid.org/0000-0003-3989-3400","affiliations":[{"raw_affiliation_string":"Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland","institution_ids":["https://openalex.org/I686019","https://openalex.org/I1300393620"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071326449","display_name":"Damian Ledzi\u0144ski","orcid":"https://orcid.org/0000-0003-0796-4390"},"institutions":[{"id":"https://openalex.org/I1300393620","display_name":"Bydgoszcz University of Science and Technology","ror":"https://ror.org/049eq0c58","country_code":"PL","type":"education","lineage":["https://openalex.org/I1300393620"]},{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Damian Ledzi\u0144ski","raw_affiliation_strings":["Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland"],"raw_orcid":"https://orcid.org/0000-0003-0796-4390","affiliations":[{"raw_affiliation_string":"Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland","institution_ids":["https://openalex.org/I686019","https://openalex.org/I1300393620"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084203907"],"corresponding_institution_ids":["https://openalex.org/I1300393620","https://openalex.org/I686019"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":16.5269,"has_fulltext":false,"cited_by_count":161,"citation_normalized_percentile":{"value":0.99512044,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"23","issue":"9","first_page":"1121","last_page":"1121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9958999752998352,"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"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7711800932884216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6970173120498657},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6748526692390442},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5810022354125977},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5637112855911255},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5090484023094177},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4983205795288086},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43783220648765564},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.337307333946228}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7711800932884216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6970173120498657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6748526692390442},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5810022354125977},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5637112855911255},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5090484023094177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4983205795288086},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43783220648765564},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.337307333946228},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/e23091121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091121","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1121/pdf?version=1630636250","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34573746","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34573746","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:c782988eb9b84c4db16455456b6b7187","is_oa":true,"landing_page_url":"https://doaj.org/article/c782988eb9b84c4db16455456b6b7187","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":"Entropy, Vol 23, Iss 9, p 1121 (2021)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:7357732","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC8469424","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1099-4300/23/9/1121/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e23091121","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 23; Issue 9; Pages: 1121","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8469424","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8469424","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23091121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091121","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1121/pdf?version=1630636250","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3197632104.pdf","grobid_xml":"https://content.openalex.org/works/W3197632104.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1576089372","https://openalex.org/W1689977300","https://openalex.org/W1862394037","https://openalex.org/W1988649197","https://openalex.org/W1990404694","https://openalex.org/W1995875735","https://openalex.org/W2014683958","https://openalex.org/W2073962065","https://openalex.org/W2108974680","https://openalex.org/W2122882636","https://openalex.org/W2140120821","https://openalex.org/W2156876426","https://openalex.org/W2162800060","https://openalex.org/W2194775991","https://openalex.org/W2586880591","https://openalex.org/W2747849569","https://openalex.org/W2791453970","https://openalex.org/W2887814324","https://openalex.org/W2964052309","https://openalex.org/W2993993911","https://openalex.org/W2996304749","https://openalex.org/W3027572331","https://openalex.org/W3084949122","https://openalex.org/W3109414960","https://openalex.org/W3118353113","https://openalex.org/W3118604399","https://openalex.org/W3119263925","https://openalex.org/W3120056192","https://openalex.org/W3133814784","https://openalex.org/W3142998727","https://openalex.org/W3164385802","https://openalex.org/W3165106054","https://openalex.org/W3170962448","https://openalex.org/W4229503723","https://openalex.org/W6678323213","https://openalex.org/W6811229795"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0,17,52,94,112,125,136],"analysis":[1],"and":[2,82,101,109,119],"processing":[3],"of":[4,14,20,48,106,122,160],"ECG":[5,50],"signals":[6],"are":[7],"a":[8,38,62,143],"key":[9],"approach":[10],"in":[11,22,61,104],"the":[12,45,58,71,75,78,83,86,132,150,156],"diagnosis":[13],"cardiovascular":[15],"diseases.":[16],"main":[18],"field":[19],"work":[21],"this":[23,36],"area":[24],"is":[25,28],"classification,":[26],"which":[27],"increasingly":[29],"supported":[30],"by":[31],"machine":[32],"learning-based":[33],"algorithms.":[34],"In":[35],"work,":[37],"deep":[39],"neural":[40,66],"network":[41,67,127,138],"was":[42,54,96],"developed":[43],"for":[44,116],"automatic":[46],"classification":[47,134],"primary":[49],"signals.":[51],"research":[53],"carried":[55],"out":[56],"on":[57,74,80,85],"data":[59],"contained":[60],"PTB-XL":[63],"database.":[64],"Three":[65],"architectures":[68],"were":[69,114],"proposed:":[70],"first":[72],"based":[73],"convolutional":[76,87,126,137],"network,":[77,88],"second":[79],"SincNet,":[81],"third":[84],"but":[89,148],"with":[90,128],"additional":[91],"entropy-based":[92,140],"features.":[93],"dataset":[95],"divided":[97],"into":[98],"training,":[99],"validation,":[100],"test":[102],"sets":[103],"proportions":[105],"70%,":[107],"15%,":[108,110],"respectively.":[111],"studies":[113],"conducted":[115],"2,":[117],"5,":[118],"20":[120],"classes":[121],"disease":[123],"entities.":[124],"entropy":[129],"features":[130,141],"obtained":[131,142],"best":[133],"result.":[135],"without":[139],"slightly":[144],"less":[145],"successful":[146],"result,":[147],"had":[149],"highest":[151],"computational":[152],"efficiency,":[153],"due":[154],"to":[155],"significantly":[157],"lower":[158],"number":[159],"neurons.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":47},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}