{"id":"https://openalex.org/W3111543990","doi":"https://doi.org/10.1109/sccc51225.2020.9281168","title":"Predicting cardiovascular disease by combining optimal feature selection methods with machine learning","display_name":"Predicting cardiovascular disease by combining optimal feature selection methods with machine learning","publication_year":2020,"publication_date":"2020-11-16","ids":{"openalex":"https://openalex.org/W3111543990","doi":"https://doi.org/10.1109/sccc51225.2020.9281168","mag":"3111543990"},"language":"en","primary_location":{"id":"doi:10.1109/sccc51225.2020.9281168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sccc51225.2020.9281168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077607460","display_name":"Mauricio Rodriguez Segura","orcid":null},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Mauricio Rodriguez Segura","raw_affiliation_strings":["Universidad Andres Bello, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Andres Bello, Santiago, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030296026","display_name":"Orietta Nicolis","orcid":"https://orcid.org/0000-0001-8046-6983"},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Orietta Nicolis","raw_affiliation_strings":["Facultad de Ingenier\u00eda, Universidad Andres Bello, Vi\u00f1a del Mar, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facultad de Ingenier\u00eda, Universidad Andres Bello, Vi\u00f1a del Mar, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020681737","display_name":"Billy Peralta Marquez","orcid":null},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Billy Peralta Marquez","raw_affiliation_strings":["Facultad de Ingenier\u00eda, Universidad Andres Bello, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facultad de Ingenier\u00eda, Universidad Andres Bello, Santiago, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037807429","display_name":"Juan Carrillo Az\u00f3car","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109374","display_name":"Hospital Luis Calvo Mackenna","ror":"https://ror.org/02k2v9264","country_code":"CL","type":"healthcare","lineage":["https://openalex.org/I4210109374"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Juan Carrillo Azocar","raw_affiliation_strings":["Hospital Dr. Carlos Cisternas de Calama, Calama, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hospital Dr. Carlos Cisternas de Calama, Calama, Chile","institution_ids":["https://openalex.org/I4210109374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.35,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80775717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9984999895095825,"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":0.9984999895095825,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9465000033378601,"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/feature-selection","display_name":"Feature selection","score":0.7682659029960632},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7485108375549316},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7476630806922913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.71140056848526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6878994703292847},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6613489985466003},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6107450723648071},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5473806858062744},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5421434640884399},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5128850936889648},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46009084582328796},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.42819860577583313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4237281382083893}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7682659029960632},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7485108375549316},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7476630806922913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.71140056848526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6878994703292847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6613489985466003},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6107450723648071},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5473806858062744},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5421434640884399},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5128850936889648},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46009084582328796},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.42819860577583313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4237281382083893},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sccc51225.2020.9281168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sccc51225.2020.9281168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 39th International Conference of the Chilean Computer Science Society (SCCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W160785014","https://openalex.org/W1993220166","https://openalex.org/W2020712165","https://openalex.org/W2118978333","https://openalex.org/W2131659142","https://openalex.org/W2295124130","https://openalex.org/W2508494164","https://openalex.org/W2605253636","https://openalex.org/W2743263355","https://openalex.org/W2897948478","https://openalex.org/W2904418346","https://openalex.org/W2939211291","https://openalex.org/W2946752003","https://openalex.org/W2995911330","https://openalex.org/W6606539394"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811","https://openalex.org/W4367335949","https://openalex.org/W3089416646","https://openalex.org/W4380048833","https://openalex.org/W4393601998"],"abstract_inverted_index":{"Cardiovascular":[0],"Disease":[1],"(CVD)":[2],"is":[3],"one":[4],"of":[5,9,109],"the":[6,12,45,53,73,76,110,114,122,126,131,139],"main":[7],"causes":[8],"death":[10],"in":[11,142],"world.":[13],"Early":[14],"detection":[15],"could":[16,69],"prevent":[17],"deaths":[18],"associated":[19],"to":[20,64,72],"cardiac":[21],"problems.":[22],"In":[23],"this":[24],"work,":[25],"we":[26],"propose":[27],"a":[28],"methodology":[29],"based":[30],"on":[31],"data":[32],"pre-processing":[33],"and":[34,57,98,113,135],"Machine":[35,96],"Learning":[36],"(ML)":[37],"techniques":[38],"for":[39,81,120],"predicting":[40],"cardiovascular":[41],"disease,":[42],"by":[43],"using":[44],"Sleep":[46],"Heart":[47],"Health":[48],"Study":[49],"(SHHS)":[50],"dataset.":[51],"First,":[52],"principal":[54],"component":[55],"analysis":[56],"lowest":[58],"p-value":[59],"logistic":[60],"regression":[61],"are":[62,79],"applied":[63],"select":[65],"optimal":[66],"features":[67,78],"which":[68],"be":[70],"related":[71],"CVD.":[74],"Then,":[75],"selected":[77],"used":[80,119],"training":[82,123],"four":[83],"ML":[84],"algorithms:":[85],"Na\u00efve":[86],"Bayes":[87],"(NB),":[88],"Feed":[89],"Forward":[90],"Neural":[91],"Networks":[92],"(NN),":[93],"Support":[94],"Vector":[95],"(SVM)":[97],"Random":[99],"Forest":[100],"(RF).":[101],"A":[102],"binary":[103],"feature":[104],"was":[105],"considered":[106],"as":[107],"output":[108],"proposed":[111,127],"models":[112],"SMOTE":[115],"sampling":[116],"has":[117],"been":[118],"balancing":[121],"set.":[124],"Among":[125],"methods,":[128],"NN":[129],"provided":[130],"best":[132],"accuracy":[133],"(0.81)":[134],"AUC":[136],"(0.76)":[137],"outperforming":[138],"results":[140],"obtained":[141],"other":[143],"studies.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
