{"id":"https://openalex.org/W2770659697","doi":"https://doi.org/10.1109/icmlc.2017.8107751","title":"Heart disease classification based on feature fusion","display_name":"Heart disease classification based on feature fusion","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2770659697","doi":"https://doi.org/10.1109/icmlc.2017.8107751","mag":"2770659697"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2017.8107751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2017.8107751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Machine Learning and Cybernetics (ICMLC)","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/A5047659429","display_name":"Tingting Zhao","orcid":"https://orcid.org/0000-0003-3787-2016"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting-Ting Zhao","raw_affiliation_strings":["East China University of Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu-Bo Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Bo Yuan","raw_affiliation_strings":["East China University of Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350000","display_name":"Yingjie Wang","orcid":"https://orcid.org/0000-0002-1054-4197"},"institutions":[{"id":"https://openalex.org/I4210098460","display_name":"Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/00z27jk27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210098460"]},{"id":"https://openalex.org/I4210149132","display_name":"Shuguang Hospital","ror":"https://ror.org/03n35e656","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210149132"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying-Jie Wang","raw_affiliation_strings":["ShuGuang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShuGuang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210149132","https://openalex.org/I4210098460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069150137","display_name":"Ju Gao","orcid":"https://orcid.org/0000-0001-7063-7574"},"institutions":[{"id":"https://openalex.org/I4210098460","display_name":"Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/00z27jk27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210098460"]},{"id":"https://openalex.org/I4210149132","display_name":"Shuguang Hospital","ror":"https://ror.org/03n35e656","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210149132"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ju Gao","raw_affiliation_strings":["ShuGuang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShuGuang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210149132","https://openalex.org/I4210098460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085592276","display_name":"Ping He","orcid":"https://orcid.org/0000-0001-7340-9606"},"institutions":[{"id":"https://openalex.org/I4210121283","display_name":"Shanghai Hospital Development Center","ror":"https://ror.org/02zrtve16","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210121283"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping He","raw_affiliation_strings":["Shanghai Hospital Development Center, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Hospital Development Center, Shanghai, China","institution_ids":["https://openalex.org/I4210121283"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"42","issue":null,"first_page":"111","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9958000183105469,"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":0.9958000183105469,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9722999930381775,"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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/canonical-correlation","display_name":"Canonical correlation","score":0.7719365358352661},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7042455673217773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6661645174026489},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6638692617416382},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6443271636962891},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6223961114883423},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.595638632774353},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5550515651702881},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.5529167056083679},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5522058010101318},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.543225109577179},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.490607887506485},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48657500743865967},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4220356047153473},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41303524374961853},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.41203171014785767}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.7719365358352661},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7042455673217773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6661645174026489},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6638692617416382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6443271636962891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6223961114883423},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.595638632774353},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5550515651702881},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.5529167056083679},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5522058010101318},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.543225109577179},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.490607887506485},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48657500743865967},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4220356047153473},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41303524374961853},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.41203171014785767},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/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/icmlc.2017.8107751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2017.8107751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1507701463","https://openalex.org/W1540278001","https://openalex.org/W1548842533","https://openalex.org/W1995013009","https://openalex.org/W2033823371","https://openalex.org/W2100235303","https://openalex.org/W2102544846","https://openalex.org/W2134262590","https://openalex.org/W2171146155","https://openalex.org/W2181803588","https://openalex.org/W2200437160","https://openalex.org/W2322029007","https://openalex.org/W2325388807","https://openalex.org/W2338401594","https://openalex.org/W2396022766","https://openalex.org/W2503261288","https://openalex.org/W2554767134","https://openalex.org/W2593801568","https://openalex.org/W6630315605","https://openalex.org/W6675403808"],"related_works":["https://openalex.org/W1565185441","https://openalex.org/W2392963705","https://openalex.org/W2107349454","https://openalex.org/W2382278777","https://openalex.org/W2167403502","https://openalex.org/W1964260090","https://openalex.org/W2353240132","https://openalex.org/W1486178390","https://openalex.org/W2375932290","https://openalex.org/W1964755555"],"abstract_inverted_index":{"Heart":[0],"disease":[1,64,130],"classification":[2,20,65],"is":[3,21,31,119,127,144],"one":[4,126],"of":[5,19,142],"the":[6,17,84,114,124,140,145],"most":[7],"important":[8],"topics":[9],"in":[10],"clinical":[11],"decision":[12],"support":[13,67],"systems":[14],"(CDSS).":[15],"However,":[16],"performance":[18,141],"greatly":[22],"affected":[23],"by":[24,66,99],"feature":[25],"selection.":[26],"Canonical":[27],"correlation":[28,55],"analysis":[29,56],"(CCA)":[30],"a":[32],"popular":[33],"method":[34],"to":[35,58,82,112],"extract":[36],"effective":[37],"features":[38,61],"from":[39,120],"two":[40,88,109],"relevant":[41],"data":[42,85,110,131],"sets.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"employ":[48],"discriminant":[49],"minimum":[50],"class":[51],"locality":[52],"preserving":[53],"canonical":[54],"(DMPCCA)":[57],"get":[59],"useful":[60],"and":[62,77,91,95,105],"finish":[63],"vector":[68],"machine":[69],"(SVM).":[70],"Normalized":[71],"mutual":[72],"information":[73,78],"based":[74],"on":[75],"entropies":[76],"gains":[79],"are":[80,97],"used":[81],"divide":[83],"sets":[86,111],"into":[87],"views":[89],"(X1":[90],"X2).":[92],"Features":[93],"extraction":[94],"fusion":[96],"implemented":[98],"different":[100],"methods,":[101],"including":[102],"CCA,":[103],"DMPCCA":[104,143],"PCA.":[106],"We":[107],"select":[108],"test":[113],"performance.":[115],"One":[116],"(1329":[117],"patients)":[118],"Shanghai":[121],"Shuguang":[122],"Hospital,":[123],"another":[125],"UCI":[128],"heart":[129],"set":[132],"(270":[133],"patients).":[134],"The":[135],"experimental":[136],"results":[137],"show":[138],"that":[139],"best.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
