{"id":"https://openalex.org/W7163874325","doi":"https://doi.org/10.1186/s12911-026-03608-9","title":"Data balancing improves mortality prediction for emergency department patients","display_name":"Data balancing improves mortality prediction for emergency department patients","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7163874325","doi":"https://doi.org/10.1186/s12911-026-03608-9","pmid":"https://pubmed.ncbi.nlm.nih.gov/42260645"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-026-03608-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03608-9","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s12911-026-03608-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078083159","display_name":"Chinyang Henry Tseng","orcid":"https://orcid.org/0000-0002-5403-0665"},"institutions":[{"id":"https://openalex.org/I99613584","display_name":"National Taipei University","ror":"https://ror.org/03e29r284","country_code":"TW","type":"education","lineage":["https://openalex.org/I99613584"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chinyang Henry Tseng","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan. tsengcyt@gm.ntpu.edu.tw"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan. tsengcyt@gm.ntpu.edu.tw","institution_ids":["https://openalex.org/I99613584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088705597","display_name":"Yu-Sheng Lo","orcid":"https://orcid.org/0000-0002-6915-509X"},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Sheng Lo","raw_affiliation_strings":["Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. Loyusen@tmu.edu.tw"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. Loyusen@tmu.edu.tw","institution_ids":["https://openalex.org/I47519274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138131614","display_name":"Yu-Juin Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]},{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Juin Lin","raw_affiliation_strings":["Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","institution_ids":["https://openalex.org/I47519274"]},{"raw_affiliation_string":"Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043344757","display_name":"Yi-Hsueh Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]},{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Hsueh Liao","raw_affiliation_strings":["Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","institution_ids":["https://openalex.org/I47519274"]},{"raw_affiliation_string":"Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138157342","display_name":"Chin-Hsin Tai","orcid":null},"institutions":[{"id":"https://openalex.org/I99613584","display_name":"National Taipei University","ror":"https://ror.org/03e29r284","country_code":"TW","type":"education","lineage":["https://openalex.org/I99613584"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Hsin Tai","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I99613584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138152055","display_name":"Ray-Jade Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]},{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ray-Jade Chen","raw_affiliation_strings":["Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan","Taipei Medical University Hospital, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan","institution_ids":["https://openalex.org/I47519274"]},{"raw_affiliation_string":"Taipei Medical University Hospital, Taipei, Taiwan","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138193301","display_name":"Juinn-Yih Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I173093425","display_name":"Chang Gung University","ror":"https://ror.org/00d80zx46","country_code":"TW","type":"education","lineage":["https://openalex.org/I173093425"]},{"id":"https://openalex.org/I4210111603","display_name":"Keelung Chang Gung Memorial Hospital","ror":"https://ror.org/020dg9f27","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210111603"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Juinn-Yih Wu","raw_affiliation_strings":["Chang Gung University College of Medicine, Kaohsiung, Taiwan","Department of Emergency Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang Gung University College of Medicine, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I173093425"]},{"raw_affiliation_string":"Department of Emergency Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan","institution_ids":["https://openalex.org/I4210111603"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138157845","display_name":"Hsin-Che Chien","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]},{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsin-Che Chien","raw_affiliation_strings":["Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan","institution_ids":["https://openalex.org/I47519274"]},{"raw_affiliation_string":"Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138123199","display_name":"Kuan-Han Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210093821","display_name":"Kaohsiung Chang Gung Memorial Hospital","ror":"https://ror.org/00k194y12","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210093821"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Kuan-Han Wu","raw_affiliation_strings":["Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital Kaohsiung Municipal Feng Shan Hospital - Under the management of Chang Gung Medical Foundation, Chang Gung University College of Medicine, Kaohsiung City, Taiwan. hayatowu1120@gmail.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital Kaohsiung Municipal Feng Shan Hospital - Under the management of Chang Gung Medical Foundation, Chang Gung University College of Medicine, Kaohsiung City, Taiwan. hayatowu1120@gmail.com","institution_ids":["https://openalex.org/I4210093821"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138144482","display_name":"Shy-Shin Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]},{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Shy-Shin Chang","raw_affiliation_strings":["Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan. sschang0529@gmail.com","Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan. sschang0529@gmail.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, No. 252, Wuxing St, Xinyi District, Taipei, 110, Taiwan. sschang0529@gmail.com","institution_ids":["https://openalex.org/I47519274"]},{"raw_affiliation_string":"Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan. sschang0529@gmail.com","institution_ids":["https://openalex.org/I2802331550"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5078083159","https://openalex.org/A5088705597","https://openalex.org/A5138123199","https://openalex.org/A5138144482"],"corresponding_institution_ids":["https://openalex.org/I2802331550","https://openalex.org/I4210093821","https://openalex.org/I47519274","https://openalex.org/I99613584"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64518031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.1573999971151352,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.1573999971151352,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T11095","display_name":"Emergency and Acute Care Studies","score":0.14560000598430634,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency 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/T13702","display_name":"Machine Learning in Healthcare","score":0.1273999959230423,"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/emergency-department","display_name":"Emergency department","score":0.7314000129699707},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.6184999942779541},{"id":"https://openalex.org/keywords/medline","display_name":"MEDLINE","score":0.32710000872612},{"id":"https://openalex.org/keywords/patient-data","display_name":"Patient data","score":0.30559998750686646},{"id":"https://openalex.org/keywords/health-services-research","display_name":"Health services research","score":0.28850001096725464},{"id":"https://openalex.org/keywords/informatics","display_name":"Informatics","score":0.2752000093460083}],"concepts":[{"id":"https://openalex.org/C2780724011","wikidata":"https://www.wikidata.org/wiki/Q1295316","display_name":"Emergency department","level":2,"score":0.7314000129699707},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6599000096321106},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.6184999942779541},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.5990999937057495},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.5270000100135803},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C3018822202","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Patient data","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C2780877353","wikidata":"https://www.wikidata.org/wiki/Q2518253","display_name":"Health services research","level":3,"score":0.28850001096725464},{"id":"https://openalex.org/C191630685","wikidata":"https://www.wikidata.org/wiki/Q4027615","display_name":"Informatics","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C167135981","wikidata":"https://www.wikidata.org/wiki/Q2146302","display_name":"Retrospective cohort study","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C545288138","wikidata":"https://www.wikidata.org/wiki/Q860447","display_name":"Emergency medical services","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C179755657","wikidata":"https://www.wikidata.org/wiki/Q58702","display_name":"Mortality rate","level":2,"score":0.2558000087738037}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000096924","descriptor_name":"Emergency Room Visits","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000096924","descriptor_name":"Emergency Room Visits","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000096924","descriptor_name":"Emergency Room Visits","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013624","descriptor_name":"Taiwan","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D013624","descriptor_name":"Taiwan","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D013624","descriptor_name":"Taiwan","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D017052","descriptor_name":"Hospital Mortality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017052","descriptor_name":"Hospital Mortality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017052","descriptor_name":"Hospital Mortality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-026-03608-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03608-9","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:42260645","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42260645","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC medical informatics and decision making","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:0ea3f460bb274d678ef338f32e9d292a","is_oa":false,"landing_page_url":"https://doaj.org/article/0ea3f460bb274d678ef338f32e9d292a","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Informatics and Decision Making, Vol 26, Iss 1 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13274082","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13274082/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-026-03608-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03608-9","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.49825337529182434,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G7737914939","display_name":"Application of Innovative Numerical Interpretable Deep Learning Combined with External Data for Comparing Palliative Care Needs Assessment in Non-Cancerous End-Stage Organ Failure Patients","funder_award_id":"NSTC113-2314-B038-092","funder_id":"https://openalex.org/F2461203286","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F2461203286","display_name":"National Science and Technology Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1988790447","https://openalex.org/W1993220166","https://openalex.org/W2148143831","https://openalex.org/W2217007515","https://openalex.org/W2295598076","https://openalex.org/W2767106145","https://openalex.org/W2770176207","https://openalex.org/W2772832743","https://openalex.org/W2903950532","https://openalex.org/W2911964244","https://openalex.org/W2929110666","https://openalex.org/W3097457142","https://openalex.org/W3106681350","https://openalex.org/W3107932444","https://openalex.org/W3138106125","https://openalex.org/W3153015596","https://openalex.org/W3194374030","https://openalex.org/W3197153878","https://openalex.org/W3199503892","https://openalex.org/W3210820305","https://openalex.org/W4200139321","https://openalex.org/W4385502364","https://openalex.org/W4386046176","https://openalex.org/W4386521649","https://openalex.org/W4388410339","https://openalex.org/W4389481977","https://openalex.org/W4408277690"],"related_works":[],"abstract_inverted_index":{"BACKGROUND:":[0],"Accurate":[1],"patient":[2,60],"mortality":[3,42,61,94,193,242,302],"prediction":[4,18,62],"is":[5,35,139,175],"crucial":[6],"in":[7,22,28,90,179,191,217,240,297],"the":[8,65,140,170,180,188,218,223,246,259,266,281,293,298],"emergency":[9,14],"department":[10],"(ED)":[11],"to":[12,53],"improve":[13],"healthcare":[15],"services.":[16],"Current":[17],"models":[19],"are":[20,44,205,210,316],"limited":[21],"both":[23],"accuracy":[24,58],"and":[25,56,63,84,100,103,106,121,160,200,207,215,228,230,253,283,306,313],"practicality,":[26],"particularly":[27],"identifying":[29],"high-risk":[30],"patients":[31],"early.":[32],"Machine":[33],"Learning":[34],"deeply":[36],"affected":[37],"by":[38,183,262],"data":[39,68,109,234],"quality":[40],"because":[41],"samples":[43],"significantly":[45],"fewer":[46],"than":[47,177,213,226,292,319],"survival":[48],"samples.":[49],"This":[50,72],"study":[51,73,182,261],"aimed":[52],"achieve":[54],"balanced":[55,212,272,311,327],"better":[57,176,224,275,290,330],"of":[59,67],"evaluate":[64],"effectiveness":[66],"balancing":[69,110,235],"methods.":[70],"METHODS:":[71],"analyzed":[74],"2,437,341":[75],"non-traumatic":[76],"adult":[77],"ED":[78],"visit":[79],"records":[80],"collected":[81],"between":[82],"2008":[83],"2016":[85],"from":[86],"five":[87],"medical":[88],"centers":[89],"Taiwan,":[91],"including":[92],"four":[93],"timeframes:":[95],"death":[96],"within":[97],"24,":[98],"72,":[99],"168":[101],"h,":[102],"final":[104],"death,":[105],"evaluated":[107],"three":[108],"methods:":[111],"Random":[112,122,128],"Under":[113],"Sampling":[114,124],"(RUS),":[115],"Synthesized":[116],"Minority":[117],"Oversampling":[118],"Technique":[119],"(SMOTE),":[120],"Over":[123],"(ROS).":[125],"We":[126],"adopted":[127],"Forest":[129],"(RF),":[130],"AdaBoost":[131,156],"(ADA),":[132],"XG":[133],"Boost":[134],"(XGB).":[135],"Logistic":[136],"Regression":[137],"(LR)":[138],"meta":[141],"learner":[142],"for":[143,280],"these":[144],"models.":[145],"Besides,":[146,321],"we":[147],"performed":[148],"feature":[149,267,276,322,331],"importance":[150,268,277,323,332],"analysis":[151,269,324],"based":[152],"on":[153],"RF,":[154],"ADA,":[155],"with":[157,167,258,304],"BootStrap":[158],"(ADA-BS),":[159],"Information":[161],"Gain":[162],"(IG).":[163],"RESULTS:":[164],"Our":[165,195,287,308],"model":[166],"XGB":[168,239,305],"achieved":[169,245,251,255],"best":[171,247],"AUROC,":[172,248],"91.41%,":[173],"which":[174,209,315],"90.2%":[178],"previous":[181,219,260,294],"Wu":[184],"et":[185,264],"al.":[186],"using":[187],"same":[189],"dataset":[190,273,328],"168-hour":[192],"timeframe.":[194],"True":[196,201],"Positive":[197],"Rate":[198,203],"(TPR)":[199],"Negative":[202],"(TNR)":[204],"79.88%":[206],"86.73%,":[208],"more":[211,317],"25%":[214],"100%":[216],"study.":[220],"ROS":[221,244],"achieves":[222,289,310],"results":[225],"RUS":[227,250],"SMOTE":[229,254],"becomes":[231],"our":[232,271,326],"primary":[233],"method.":[236],"While":[237],"adopting":[238],"24-hour":[241],"timeframes,":[243],"93.72%,":[249],"93.61%":[252],"91.73%.":[256],"Compared":[257],"Lin":[263],"al.,":[265],"shows":[270,325],"has":[274,329],"impacts,":[278],"especially":[279,296],"\"Age\"":[282],"\"Triage\"":[284],"features.":[285],"CONCLUSION:":[286],"method":[288,309],"AUROC":[291],"study,":[295],"long":[299],"challenging":[300],"death-hour":[301],"timeframe":[303],"ROS.":[307],"TPR":[312],"TNR,":[314],"practical":[318],"AUROC.":[320],"impacts.":[333]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-06-09T00:00:00"}
