{"id":"https://openalex.org/W4386580466","doi":"https://doi.org/10.1186/s40537-023-00820-6","title":"Optical electrocardiogram based heart disease prediction using hybrid deep learning","display_name":"Optical electrocardiogram based heart disease prediction using hybrid deep learning","publication_year":2023,"publication_date":"2023-09-09","ids":{"openalex":"https://openalex.org/W4386580466","doi":"https://doi.org/10.1186/s40537-023-00820-6"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-023-00820-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00820-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00820-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00820-6","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023515757","display_name":"Avinash Golande","orcid":"https://orcid.org/0000-0001-6245-0259"},"institutions":[{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Avinash L. Golande","raw_affiliation_strings":["Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, AP, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, AP, India","institution_ids":["https://openalex.org/I875944469"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057868171","display_name":"T. Pavankumar","orcid":null},"institutions":[{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"T. Pavankumar","raw_affiliation_strings":["Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, AP, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, AP, India","institution_ids":["https://openalex.org/I875944469"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023515757"],"corresponding_institution_ids":["https://openalex.org/I875944469"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":4.9653,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.96272281,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"10","issue":"1","first_page":null,"last_page":null},"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":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.802718997001648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7647526264190674},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7624123096466064},{"id":"https://openalex.org/keywords/heartbeat","display_name":"Heartbeat","score":0.6956250071525574},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.6152043342590332},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5872835516929626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5702649354934692},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5438436269760132},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4871351420879364},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4816838204860687},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.467551589012146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4378495514392853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4351934790611267}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.802718997001648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7647526264190674},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7624123096466064},{"id":"https://openalex.org/C13852961","wikidata":"https://www.wikidata.org/wiki/Q17021880","display_name":"Heartbeat","level":2,"score":0.6956250071525574},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6152043342590332},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5872835516929626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5702649354934692},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5438436269760132},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4871351420879364},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4816838204860687},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.467551589012146},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4378495514392853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4351934790611267},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-023-00820-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00820-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00820-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2c3552cd42654ac0a30ccbc2782164c9","is_oa":true,"landing_page_url":"https://doaj.org/article/2c3552cd42654ac0a30ccbc2782164c9","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":"Journal of Big Data, Vol 10, Iss 1, Pp 1-13 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-023-00820-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00820-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00820-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386580466.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1868102512","https://openalex.org/W1996894363","https://openalex.org/W2017487767","https://openalex.org/W2025492635","https://openalex.org/W2061185532","https://openalex.org/W2101166342","https://openalex.org/W2103308415","https://openalex.org/W2152865365","https://openalex.org/W2162693370","https://openalex.org/W2547384925","https://openalex.org/W2592521712","https://openalex.org/W2607867882","https://openalex.org/W2809982758","https://openalex.org/W2961638199","https://openalex.org/W2986898183","https://openalex.org/W2995456481","https://openalex.org/W2999069903","https://openalex.org/W3017101319","https://openalex.org/W3034033080","https://openalex.org/W3082071380","https://openalex.org/W3120030679","https://openalex.org/W3127743958","https://openalex.org/W3162429572","https://openalex.org/W4210393027","https://openalex.org/W4220809479","https://openalex.org/W4221066151","https://openalex.org/W4221130119"],"related_works":["https://openalex.org/W4385543909","https://openalex.org/W3039320222","https://openalex.org/W3199640442","https://openalex.org/W1898280036","https://openalex.org/W2315807364","https://openalex.org/W2382278803","https://openalex.org/W2113096447","https://openalex.org/W2803040299","https://openalex.org/W2376695684","https://openalex.org/W2965782936"],"abstract_inverted_index":{"Abstract":[0],"The":[1,36,91,113,181],"diagnosis":[2],"and":[3,34,43,122,131,154,198],"categorization":[4],"of":[5,73,94,117,183,195,201],"cardiac":[6,26],"disease":[7,27,56,104,162],"using":[8,64,107,147],"the":[9,74,78,95,101,136,164,172,184,188,193,199,210],"low-cost":[10],"tool":[11],"electrocardiogram":[12],"(ECG)":[13],"becomes":[14],"an":[15,125],"intriguing":[16],"study":[17],"topic":[18],"when":[19,207],"contemplating":[20],"intelligent":[21],"healthcare":[22],"applications.":[23],"An":[24],"ECG-based":[25,54,102],"prediction":[28],"system":[29],"must":[30],"be":[31],"automated,":[32],"accurate,":[33],"lightweight.":[35],"deep":[37,50,66,173],"learning":[38,51,67,174],"methods":[39],"recently":[40],"achieved":[41],"automation":[42],"accuracy":[44],"across":[45],"multiple":[46],"domains.":[47],"However,":[48],"applying":[49],"for":[52],"automatic":[53],"heart":[55,103,161],"classification":[57,105],"is":[58,85,98,168],"a":[59,82,108,144,148],"challenging":[60],"research":[61],"problem.":[62],"Because":[63],"solely":[65],"approaches":[68],"failed":[69],"to":[70,87,99,128,209],"detect":[71],"all":[72],"important":[75],"beats":[76,151],"from":[77],"input":[79],"ECG":[80,126,150],"signal,":[81],"hybrid":[83,109,119,145,165],"strategy":[84],"necessary":[86],"improve":[88],"detection":[89],"efficiency.":[90],"main":[92],"objective":[93],"proposed":[96,114,189],"model":[97,115,190],"enhance":[100],"efficiency":[106],"feature":[110,120,166],"engineering":[111],"approach.":[112],"consists":[116],"pre-processing,":[118],"engineering,":[121],"classification.":[123],"Pre-processing":[124],"aims":[127],"eliminate":[129],"powerline":[130],"baseline":[132],"interference":[133],"without":[134],"disrupting":[135],"heartbeat.":[137],"To":[138],"efficiently":[139],"classify":[140],"data,":[141],"we":[142],"design":[143],"approach":[146],"conventional":[149],"extraction":[152],"algorithm":[153],"Convolutional":[155],"Neural":[156],"Network":[157],"(CNN)-based":[158],"features.":[159],"For":[160],"prediction,":[163],"vector":[167],"fed":[169],"successively":[170],"into":[171],"classifier":[175],"Long":[176],"Term":[177],"Short":[178],"Memory":[179],"(LSTM).":[180],"results":[182],"simulations":[185],"show":[186],"that":[187],"reduces":[191],"both":[192],"number":[194],"diagnostic":[196],"errors":[197],"amount":[200],"time":[202],"spent":[203],"on":[204],"each":[205],"one":[206],"compared":[208],"existing":[211],"methods.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":12}],"updated_date":"2026-06-17T06:14:20.161405","created_date":"2025-10-10T00:00:00"}