{"id":"https://openalex.org/W4312458389","doi":"https://doi.org/10.1109/access.2022.3232307","title":"A Fully Connected Quantum Convolutional Neural Network for Classifying Ischemic Cardiopathy","display_name":"A Fully Connected Quantum Convolutional Neural Network for Classifying Ischemic Cardiopathy","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312458389","doi":"https://doi.org/10.1109/access.2022.3232307"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3232307","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3232307","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://doi.org/10.1109/access.2022.3232307","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038101457","display_name":"Ubaid Ullah","orcid":"https://orcid.org/0000-0001-8149-3430"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Ubaid Ullah","raw_affiliation_strings":["EVIDA Research Group, University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"EVIDA Research Group, University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062986535","display_name":"Alain Garc\u00eda-Olea","orcid":"https://orcid.org/0000-0002-8742-0600"},"institutions":[{"id":"https://openalex.org/I4210092871","display_name":"Hospital de Basurto","ror":"https://ror.org/00j4pze04","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210092871","https://openalex.org/I4210125364"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Alain Garcia Olea Jurado","raw_affiliation_strings":["Cardiology Service, Basurto University Hospital, Bilbao, Bizkaia, Spain"],"affiliations":[{"raw_affiliation_string":"Cardiology Service, Basurto University Hospital, Bilbao, Bizkaia, Spain","institution_ids":["https://openalex.org/I4210092871"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078856392","display_name":"I Diez Gonzalez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092871","display_name":"Hospital de Basurto","ror":"https://ror.org/00j4pze04","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210092871","https://openalex.org/I4210125364"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ignacio Diez Gonzalez","raw_affiliation_strings":["Cardiology Service, Basurto University Hospital, Bilbao, Bizkaia, Spain"],"affiliations":[{"raw_affiliation_string":"Cardiology Service, Basurto University Hospital, Bilbao, Bizkaia, Spain","institution_ids":["https://openalex.org/I4210092871"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028149208","display_name":"Begonya Garc\u00eda-Zapirain","orcid":"https://orcid.org/0000-0002-9356-1186"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Begonya Garcia-Zapirain","raw_affiliation_strings":["EVIDA Research Group, University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"EVIDA Research Group, University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038101457"],"corresponding_institution_ids":["https://openalex.org/I136040515"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.0712,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.97433939,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"134592","last_page":"134605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9447000026702881,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7205392122268677},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7179569602012634},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.4390513002872467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3158225417137146},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11358228325843811}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7205392122268677},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7179569602012634},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.4390513002872467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3158225417137146},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11358228325843811},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2022.3232307","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3232307","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ebc6a0362d314a16a62a7e85d1ee2b18","is_oa":true,"landing_page_url":"https://doaj.org/article/ebc6a0362d314a16a62a7e85d1ee2b18","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access, Vol 10, Pp 134592-134605 (2022)","raw_type":"article"},{"id":"pmh:oai:zenodo.org:7945430","is_oa":true,"landing_page_url":"https://zenodo.org/record/7945430","pdf_url":"https://zenodo.org/record/7945430","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3232307","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3232307","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1974542962","display_name":null,"funder_award_id":"Sk\u0142odowska","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2689612763","display_name":null,"funder_award_id":"Marie","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7619634553","display_name":null,"funder_award_id":"847624","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321705","display_name":"Eusko Jaurlaritza","ror":"https://ror.org/00pz2fp31"},{"id":"https://openalex.org/F4320330632","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1597537144","https://openalex.org/W1990031103","https://openalex.org/W1995891440","https://openalex.org/W2037984448","https://openalex.org/W2062302861","https://openalex.org/W2083249151","https://openalex.org/W2083780116","https://openalex.org/W2104044232","https://openalex.org/W2141826465","https://openalex.org/W2296128757","https://openalex.org/W2482126025","https://openalex.org/W2546191734","https://openalex.org/W2566909686","https://openalex.org/W2600971008","https://openalex.org/W2752623698","https://openalex.org/W2767381938","https://openalex.org/W2774583472","https://openalex.org/W2790388700","https://openalex.org/W2792315573","https://openalex.org/W2795475639","https://openalex.org/W2798434869","https://openalex.org/W2808979145","https://openalex.org/W2900794383","https://openalex.org/W2901857397","https://openalex.org/W2903099708","https://openalex.org/W2903221501","https://openalex.org/W2982169647","https://openalex.org/W2987045841","https://openalex.org/W2988221611","https://openalex.org/W3042959531","https://openalex.org/W3046510752","https://openalex.org/W3047051048","https://openalex.org/W3087356534","https://openalex.org/W3100111077","https://openalex.org/W3102324541","https://openalex.org/W3104962094","https://openalex.org/W3107697696","https://openalex.org/W3108123664","https://openalex.org/W3111701537","https://openalex.org/W3129494485","https://openalex.org/W3160768652","https://openalex.org/W3168757307","https://openalex.org/W3170481436","https://openalex.org/W3177781640","https://openalex.org/W3191359713","https://openalex.org/W3192976953","https://openalex.org/W3197589015","https://openalex.org/W4206799920","https://openalex.org/W4212872196","https://openalex.org/W4226369590","https://openalex.org/W4241296478","https://openalex.org/W4282596355","https://openalex.org/W4285058055","https://openalex.org/W4288785604","https://openalex.org/W4291885280","https://openalex.org/W4296083357","https://openalex.org/W4297174789","https://openalex.org/W4300349831","https://openalex.org/W4385885462","https://openalex.org/W4386661611","https://openalex.org/W4389607983","https://openalex.org/W6770085649","https://openalex.org/W6770278077","https://openalex.org/W6780444736","https://openalex.org/W6800254480","https://openalex.org/W6800708485"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4293226380"],"abstract_inverted_index":{"The":[0,91,132,170,226],"prevalence":[1],"of":[2,44,62,93,114,130,134,157,213,222,275,284,288,294,312,333,342],"heart":[3],"diseases":[4],"is":[5,34,53,75,271],"rising":[6],"quickly":[7],"throughout":[8],"the":[9,17,25,30,42,59,83,88,112,139,158,174,211,233,237,245,269,276,281,300,304,313,328],"world,":[10],"which":[11],"has":[12,228,239,265],"an":[13,48],"impact":[14,67],"on":[15,68],"both":[16],"world":[18],"economy":[19],"and":[20,47,55,65,86,96,104,120,124,145,215,220,242,279,320,346],"public":[21],"health.":[22],"According":[23],"to":[24,36,57,77,81,310,331],"recent":[26],"statistical":[27],"survey":[28],"reports,":[29],"increasing":[31],"mortality":[32,89],"rate":[33],"due":[35],"high":[37,40],"blood":[38],"pressure,":[39],"cholesterol,":[41],"use":[43,78],"tobacco,":[45],"obesity,":[46],"inconsistent":[49],"pulse":[50],"rate.":[51,90],"It":[52],"difficult":[54],"time-consuming":[56],"investigate":[58],"various":[60,105],"variations":[61],"these":[63],"factors":[64],"their":[66,122],"Coronary":[69],"Artery":[70],"Disease":[71,167],"(CAD).":[72],"Therefore,":[73],"it":[74],"necessary":[76],"modern":[79],"approaches":[80],"diagnose":[82],"disease":[84],"early":[85,118,146],"minimize":[87],"fields":[92],"machine":[94,188],"learning":[95,189],"data":[97,238],"mining":[98],"have":[99],"a":[100,127,150,154,185,255,285,291],"wide":[101],"research":[102],"dimension":[103,253],"novel":[106],"techniques":[107],"that":[108,178,332],"could":[109],"help":[110],"in":[111,116,126,142,340],"prediction":[113],"CAD":[115],"its":[117],"stages":[119],"identify":[121],"patterns":[123],"behaviors":[125],"huge":[128],"amount":[129],"data.":[131],"results":[133,283],"such":[135,149],"predictions":[136],"will":[137],"aid":[138],"clinical":[140],"staff":[141],"decision":[143],"making":[144],"diagnosis.":[147],"In":[148],"scenario,":[151],"we":[152],"proposed":[153,171,305],"quantum":[155,175,224,336],"version":[156],"Fully":[159,321],"Convolutional":[160],"Neural":[161,317,323],"Network":[162,318,324],"(FCQ-CNN)":[163],"for":[164,202,217],"Ischemic":[165],"Heart":[166],"(IHD)":[168],"classification.":[169],"model":[172,227,270,306],"evaluates":[173],"circuit-based":[176],"technique":[177],"was":[179],"inspired":[180],"by":[181,231],"convolutional":[182],"neural":[183],"networks,":[184],"very":[186],"successful":[187],"model.":[190],"This":[191],"method":[192],"provides":[193],"<inline-formula":[194,203],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[195,204],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[196,205],"<tex-math":[197,206],"notation=\"LaTeX\">$O(log":[198],"(n))$":[199],"</tex-math></inline-formula>":[200,208],"depth":[201],"notation=\"LaTeX\">$n$":[207],"qubits,":[209],"reducing":[210],"number":[212],"parameters":[214],"allowing":[216],"effective":[218],"training":[219],"testing":[221,286,292],"real":[223],"devices.":[225],"been":[229,240,266],"evaluated":[230],"considering":[232],"IHD":[234],"dataset":[235,278],"after":[236],"cleaned":[241],"filtered":[243],"through":[244],"Maximally":[246],"Relevant":[247],"Minimally":[248],"Redundancy":[249],"(MRMR)":[250],"filter.":[251],"For":[252],"reduction,":[254],"Support":[256],"Vector":[257],"Machine":[258],"along":[259],"with":[260,273,290],"Recursive":[261],"Feature":[262],"Elimination":[263],"(SVM-RFE)":[264],"considered.":[267],"Initially,":[268],"tested":[272],"20%":[274],"whole":[277],"gets":[280],"promising":[282],"accuracy":[287,341],"84.6%":[289],"loss":[293],"0.28.":[295],"By":[296],"taking":[297],"into":[298],"account":[299],"same":[301],"optimal":[302],"parameters,":[303],"outcomes":[307],"are":[308],"compared":[309],"those":[311],"classical":[314],"Optimized":[315],"Convolution":[316],"(Optimized-CNN)":[319],"Connected":[322],"(FCNN)":[325],"models.":[326],"Comparing":[327],"model\u2019s":[329],"competency":[330],"earlier":[334],"published":[335],"models":[337],"yields":[338],"improvements":[339],"8.6%,":[343],"12.6%,":[344],"3.5%,":[345],"1.8%":[347],"respectively.":[348]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}