{"id":"https://openalex.org/W7127160539","doi":"https://doi.org/10.31449/inf.v50i5.10455","title":"Cardiovascular Disease Prediction via Hybrid SVM\u2013SMOTE and Sparse Autoencoder Feature Reduction with Deep MLP Classification","display_name":"Cardiovascular Disease Prediction via Hybrid SVM\u2013SMOTE and Sparse Autoencoder Feature Reduction with Deep MLP Classification","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127160539","doi":"https://doi.org/10.31449/inf.v50i5.10455"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i5.10455","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10455","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10455/6429","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/10455/6429","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045112704","display_name":"Zaid Alaa","orcid":null},"institutions":[{"id":"https://openalex.org/I47229656","display_name":"University of Kufa","ror":"https://ror.org/02dwrdh81","country_code":"IQ","type":"education","lineage":["https://openalex.org/I47229656"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Zaid Alaa","raw_affiliation_strings":["University of Kufa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kufa","institution_ids":["https://openalex.org/I47229656"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124851419","display_name":"Ali Sabah","orcid":null},"institutions":[{"id":"https://openalex.org/I47229656","display_name":"University of Kufa","ror":"https://ror.org/02dwrdh81","country_code":"IQ","type":"education","lineage":["https://openalex.org/I47229656"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Ali Sabah","raw_affiliation_strings":["University of Kufa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kufa","institution_ids":["https://openalex.org/I47229656"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47229656"],"apc_list":null,"apc_paid":null,"fwci":34.8887,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98477781,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"50","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.5892999768257141,"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":0.5892999768257141,"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":0.16290000081062317,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.06849999725818634,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/autoencoder","display_name":"Autoencoder","score":0.7843000292778015},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6365000009536743},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5907999873161316},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5328999757766724},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5266000032424927},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4968999922275543},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.47450000047683716},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4560999870300293}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7843000292778015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7315000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668000221252441},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6365000009536743},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5907999873161316},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5266000032424927},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.47450000047683716},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4560999870300293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4341000020503998},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.42640000581741333},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.41499999165534973},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4147000014781952},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29739999771118164},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i5.10455","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10455","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10455/6429","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i5.10455","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10455","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10455/6429","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5503296852111816}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127160539.pdf","grobid_xml":"https://content.openalex.org/works/W7127160539.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cardiovascular":[0],"diseases":[1],"remain":[2],"the":[3,83,97,140,144],"leading":[4],"global":[5],"cause":[6],"of":[7,102,146],"death,":[8],"demanding":[9],"diagnostic":[10],"systems":[11],"that":[12,45],"are":[13],"accurate,":[14],"interpretable,":[15],"and":[16,30,48,69,88,107,116,126,131,178],"computationally":[17],"efficient.":[18],"Traditional":[19],"machine":[20],"learning":[21],"approaches":[22],"frequently":[23],"struggle":[24],"with":[25,60,112],"class":[26,54],"imbalance,":[27],"high-dimensional":[28],"noise,":[29],"restricted":[31],"generalization":[32],"in":[33],"clinical":[34],"datasets.":[35],"To":[36],"tackle":[37],"such":[38],"issues,":[39],"we":[40],"propose":[41],"a":[42,56,70,150,175],"hybrid":[43],"framework":[44,81,173],"combines":[46],"SVM\u2013SMOTE":[47],"neighborhood":[49],"cleaning":[50],"rule":[51],"(NCL)":[52],"for":[53,65,75,181],"rebalancing,":[55],"sparse":[57],"autoencoder":[58],"(SAE)":[59],"random":[61],"forest":[62],"(RF)":[63],"selection":[64],"non-linear":[66],"feature":[67],"optimization,":[68],"class-weighted":[71],"multilayer":[72],"perceptron":[73],"(MLP)":[74],"final":[76],"classification.":[77],"We":[78],"validate":[79],"our":[80],"on":[82],"Z-Alizadeh":[84],"Sani":[85],"(54":[86],"features)":[87,91],"Cleveland":[89],"(13":[90],"datasets":[92],"under":[93],"stratified":[94],"fivefold":[95],"cross-validation,":[96],"model":[98],"attains":[99],"mean":[100],"accuracies":[101],"94.02":[103],"\u00b1":[104,109],"2.77":[105],"%":[106],"94.36":[108],"1.47":[110],"%,":[111],"AUC\u2013ROC":[113],"=":[114],"0.988":[115],"0.982,":[117],"outperforming":[118],"prior":[119],"baselines":[120],"[4,":[121],"10,":[122],"14]":[123],"by":[124],"7.6%\u201320.8%,":[125],"Bootstrap":[127],"95%":[128],"confidence":[129],"intervals":[130],"McNemar/DeLong":[132],"tests":[133],"(p":[134],"<":[135],"0.001)":[136],"confirms":[137],"significance.":[138],"Noteably,":[139],"ablation":[141],"study":[142],"demonstrates":[143],"contribution":[145],"each":[147],"module":[148],"(e.g.,":[149],"12%":[151],"accuracy":[152],"improvement":[153],"without":[154],"sampling).":[155],"The":[156,171],"optimized":[157],"MLP":[158],"reduced":[159],"false":[160],"negatives":[161],"to":[162],"~5%,":[163],"while":[164],"training":[165],"40%":[166],"faster":[167],"than":[168],"CNN\u2013LSTM":[169],"alternatives.":[170],"proposed":[172],"provides":[174],"statistically":[176],"robust":[177],"interpretable":[179],"solution":[180],"predicting":[182],"cardiovascular":[183],"disease.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-03T00:00:00"}