{"id":"https://openalex.org/W2772178448","doi":"https://doi.org/10.1109/healthcom.2017.8210761","title":"ICU mortality prediction using modified cost-sensitive PCA and chaos PSO","display_name":"ICU mortality prediction using modified cost-sensitive PCA and chaos PSO","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2772178448","doi":"https://doi.org/10.1109/healthcom.2017.8210761","mag":"2772178448"},"language":"en","primary_location":{"id":"doi:10.1109/healthcom.2017.8210761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2017.8210761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom)","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":null,"display_name":"Jiankang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankang Liu","raw_affiliation_strings":["Institute of Electronics Chinese Academy of Sciences, Beijing, China","Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031628319","display_name":"XianXiang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XianXiang Chen","raw_affiliation_strings":["Institute of Electronics Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087852871","display_name":"Zhen Fang","orcid":"https://orcid.org/0000-0003-0602-6255"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Fang","raw_affiliation_strings":["Institute of Electronics Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102018972","display_name":"Kai Tong","orcid":"https://orcid.org/0000-0002-8336-1287"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Tong","raw_affiliation_strings":["Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086761071","display_name":"Lipeng Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lipeng Fang","raw_affiliation_strings":["Institute of Electronics Chinese Academy of Sciences, Beijing, China","Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059912193","display_name":"JunXia Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124286","display_name":"The Military General Hospital of Beijing PLA","ror":"https://ror.org/0259e4473","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210124286"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"JunXia Li","raw_affiliation_strings":["Army General Hospital of PLA, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Army General Hospital of PLA, Beijing, China","institution_ids":["https://openalex.org/I4210124286"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1384,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45648292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9851999878883362,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9851999878883362,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9656999707221985,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7055215835571289},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6010653972625732},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5903632044792175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5591170191764832},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5362706780433655},{"id":"https://openalex.org/keywords/intensive-care-unit","display_name":"Intensive care unit","score":0.5313378572463989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4587145149707794},{"id":"https://openalex.org/keywords/intensive-care","display_name":"Intensive care","score":0.42317983508110046},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36879169940948486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35572943091392517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3243507742881775},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11883702874183655},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.1098652184009552}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7055215835571289},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6010653972625732},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5903632044792175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5591170191764832},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5362706780433655},{"id":"https://openalex.org/C2776376669","wikidata":"https://www.wikidata.org/wiki/Q5094647","display_name":"Intensive care unit","level":2,"score":0.5313378572463989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4587145149707794},{"id":"https://openalex.org/C2987404301","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care","level":2,"score":0.42317983508110046},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36879169940948486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35572943091392517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3243507742881775},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11883702874183655},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.1098652184009552}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/healthcom.2017.8210761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2017.8210761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W768866563","https://openalex.org/W1522684182","https://openalex.org/W2020355555","https://openalex.org/W2046788142","https://openalex.org/W2051861970","https://openalex.org/W2059115408","https://openalex.org/W2139212933","https://openalex.org/W2148603752","https://openalex.org/W2150369813","https://openalex.org/W2277786047","https://openalex.org/W2285597872","https://openalex.org/W2383686222","https://openalex.org/W2390154686","https://openalex.org/W2414616848","https://openalex.org/W2525427063","https://openalex.org/W2526177130","https://openalex.org/W2534318479","https://openalex.org/W6630988046","https://openalex.org/W6729174697","https://openalex.org/W7071374342"],"related_works":["https://openalex.org/W2474790959","https://openalex.org/W2057630253","https://openalex.org/W2331454882","https://openalex.org/W2740671600","https://openalex.org/W2327606279","https://openalex.org/W2753993308","https://openalex.org/W2274076556","https://openalex.org/W2362037864","https://openalex.org/W2761860407","https://openalex.org/W1984498786"],"abstract_inverted_index":{"The":[0,120,134],"death":[1],"of":[2,78,145,151],"the":[3,10,47,68,75,79,91,113,117,139],"patients":[4],"is":[5,54],"an":[6],"important":[7],"event":[8],"in":[9,33],"intensive":[11],"care":[12],"unit":[13],"(ICU),":[14],"mortality":[15,29,96],"risk":[16],"prediction":[17,30],"thus":[18],"offers":[19],"much":[20],"information":[21],"for":[22,99],"clinical":[23],"decision":[24],"making.":[25],"However,":[26],"Patient":[27],"ICU":[28,95],"faces":[31],"challenges":[32],"many":[34],"aspects,":[35],"such":[36],"as":[37,90,130],"high":[38],"dimensionality,":[39],"imbalance":[40],"distribution.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"modified":[46,63],"cost-sensitive":[48],"principal":[49],"component":[50],"analysis":[51],"(CSPCA),":[52],"which":[53],"denoted":[55],"by":[56],"MCSPCA,":[57],"to":[58,93,111],"solve":[59],"these":[60],"problems.":[61],"This":[62],"method":[64],"not":[65],"only":[66],"reduced":[67],"feature":[69],"dimensionality":[70],"but":[71],"also":[72],"better":[73],"handled":[74],"imbalanced":[76],"problem":[77],"benchmark":[80],"data.":[81],"A":[82],"support":[83],"vector":[84],"machine":[85],"(SVM)":[86],"model":[87,122,131,141],"was":[88,109,123],"used":[89,110],"classifier":[92],"identify":[94],"risk.":[97],"As":[98],"SVM":[100],"parameters":[101],"optimization,":[102],"a":[103],"chaos":[104],"particle":[105],"swarm":[106],"optimization":[107],"(CPSO)":[108],"optimize":[112],"penalty":[114],"parameter":[115],"and":[116,147],"kernel":[118],"parameter.":[119],"proposed":[121,140],"compared":[124],"with":[125],"several":[126],"contrast":[127],"models":[128],"(such":[129],"without":[132],"PCA).":[133],"test":[135],"results":[136],"indicate":[137],"that":[138],"showed":[142],"highest":[143],"AUC":[144],"0.7718":[146],"minimum":[148],"consumption":[149],"time":[150],"814s.":[152]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
