{"id":"https://openalex.org/W4384519248","doi":"https://doi.org/10.1109/access.2023.3296147","title":"Predicting ICU Mortality Based on Generative Adversarial Nets and Ensemble Methods","display_name":"Predicting ICU Mortality Based on Generative Adversarial Nets and Ensemble Methods","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4384519248","doi":"https://doi.org/10.1109/access.2023.3296147"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3296147","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3296147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185040.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102839009","display_name":"Mingyi Wei","orcid":"https://orcid.org/0009-0001-1683-6887"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyi Wei","raw_affiliation_strings":["Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0001-1683-6887","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010467569","display_name":"Zhejun Huang","orcid":"https://orcid.org/0000-0002-3406-2942"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhejun Huang","raw_affiliation_strings":["Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China","Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091186955","display_name":"Yuan Diping","orcid":null},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Diping Yuan","raw_affiliation_strings":["Technology and Information Center, Shenzhen Urban Public Safety Technology Institute, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology and Information Center, Shenzhen Urban Public Safety Technology Institute, Shenzhen, China","institution_ids":["https://openalex.org/I158809036"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070434985","display_name":"Lili Yang","orcid":"https://orcid.org/0000-0002-7070-9723"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Yang","raw_affiliation_strings":["Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China","Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6345,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72689017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"11","issue":null,"first_page":"76403","last_page":"76414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9991000294685364,"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":0.9991000294685364,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9890999794006348,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9692000150680542,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/computer-science","display_name":"Computer science","score":0.6853117942810059},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5849244594573975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5023360252380371},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4879712462425232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33303767442703247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6853117942810059},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5849244594573975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5023360252380371},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4879712462425232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33303767442703247}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3296147","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3296147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0ede81d0b5ab49d2a6f146dffe25c716","is_oa":true,"landing_page_url":"https://doaj.org/article/0ede81d0b5ab49d2a6f146dffe25c716","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":"IEEE Access, Vol 11, Pp 76403-76414 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3296147","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3296147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185040.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G2810916823","display_name":null,"funder_award_id":"ZDSYS20210623092007023","funder_id":"https://openalex.org/F4320336569","funder_display_name":"Shenzhen Science and Technology Innovation Program"},{"id":"https://openalex.org/G4357656554","display_name":null,"funder_award_id":"2019YFC0810705","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G80583112","display_name":null,"funder_award_id":"JCYJ20200109141218676","funder_id":"https://openalex.org/F4320336569","funder_display_name":"Shenzhen Science and Technology Innovation Program"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320336569","display_name":"Shenzhen Science and Technology Innovation Program","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384519248.pdf","grobid_xml":"https://content.openalex.org/works/W4384519248.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1550778365","https://openalex.org/W1966670930","https://openalex.org/W1982067074","https://openalex.org/W2000566182","https://openalex.org/W2004548053","https://openalex.org/W2025208635","https://openalex.org/W2032733517","https://openalex.org/W2038968264","https://openalex.org/W2067747050","https://openalex.org/W2088744061","https://openalex.org/W2097998348","https://openalex.org/W2148143831","https://openalex.org/W2155653793","https://openalex.org/W2161687618","https://openalex.org/W2170835861","https://openalex.org/W2200122354","https://openalex.org/W2295598076","https://openalex.org/W2345930594","https://openalex.org/W2412650410","https://openalex.org/W2415795929","https://openalex.org/W2462947830","https://openalex.org/W2582139224","https://openalex.org/W2729239634","https://openalex.org/W2749057300","https://openalex.org/W2766155847","https://openalex.org/W2900350809","https://openalex.org/W2913062164","https://openalex.org/W3044427673","https://openalex.org/W3121246486","https://openalex.org/W3127682585","https://openalex.org/W4247943214","https://openalex.org/W4293242440","https://openalex.org/W4298289240","https://openalex.org/W4310180477","https://openalex.org/W4312058479","https://openalex.org/W4317036905","https://openalex.org/W6637568146","https://openalex.org/W6674385629","https://openalex.org/W6733065424"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"The":[0,114,127],"intensive":[1],"care":[2],"unit":[3],"(ICU)":[4],"typically":[5],"admits":[6],"patients":[7,122],"who":[8,21],"require":[9],"urgent":[10],"medical":[11],"intervention.":[12],"Predicting":[13],"ICU":[14,38,67,163],"mortality":[15,68],"is":[16,89],"crucial":[17],"for":[18,37,65],"identifying":[19],"those":[20],"are":[22],"at":[23],"higher":[24],"risk.":[25],"Traditional":[26],"statistical":[27],"methods,":[28],"such":[29],"as":[30],"logistic":[31],"regression,":[32],"have":[33,45],"been":[34],"widely":[35],"used":[36],"survival":[39],"prediction.":[40],"However,":[41],"these":[42],"methods":[43],"often":[44],"limitations":[46],"in":[47,136],"capturing":[48],"complex":[49],"nonlinear":[50],"relationships":[51],"between":[52],"the":[53,66,74,81,133,141,153,158],"clinical":[54],"features.":[55],"A":[56],"prediction":[57,69],"model":[58,117,160],"based":[59,79],"on":[60,80],"ensemble":[61],"learning":[62],"was":[63,77,102,118],"proposed":[64,115],"problem:":[70],"MTX-stacking":[71,116,131,159],"model.":[72],"Firstly,":[73],"imbalanced":[75],"data":[76,97],"processed":[78],"modified":[82],"generative":[83],"adversarial":[84],"network":[85],"method.":[86],"This":[87],"approach":[88],"more":[90,93],"explanatory":[91],"and":[92,108,148,155],"effective":[94],"than":[95],"traditional":[96],"generation":[98],"methods.":[99],"Secondly,":[100],"XGBoost":[101],"optimized":[103],"by":[104],"tree-structured":[105],"parzen":[106],"estimator":[107],"stacking":[109],"structure":[110],"to":[111,161],"prevent":[112],"overfitting.":[113],"evaluated":[119],"using":[120],"131,051":[121],"from":[123],"MIT\u2019s":[124],"GOSSIS":[125],"initiative.":[126],"results":[128],"indicate":[129],"that":[130],"outperforms":[132],"state-of-the-art":[134],"approaches":[135],"terms":[137],"of":[138,157],"area":[139],"under":[140],"receiver":[142],"operator":[143],"characteristic":[144],"(ROC)":[145],"curve":[146],"(91.2%":[147],"90.9%).":[149],"These":[150],"findings":[151],"demonstrate":[152],"ability":[154],"efficiency":[156],"predict":[162],"mortality.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
