{"id":"https://openalex.org/W7141574662","doi":"https://doi.org/10.1186/s12911-026-03448-7","title":"Performance fairness of neural network models in early risk assessment of inpatients with varying severity: a retrospective study","display_name":"Performance fairness of neural network models in early risk assessment of inpatients with varying severity: a retrospective study","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7141574662","doi":"https://doi.org/10.1186/s12911-026-03448-7","pmid":"https://pubmed.ncbi.nlm.nih.gov/41896906"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-026-03448-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03448-7","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/s12911-026-03448-7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130720825","display_name":"Lan Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087691","display_name":"Beijing Tian Tan Hospital","ror":"https://ror.org/003regz62","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210087691"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Lan","raw_affiliation_strings":["Information Management and Data Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Management and Data Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China","institution_ids":["https://openalex.org/I4210087691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130809327","display_name":"Shixin Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I4210161892","display_name":"First People's Hospital of Chongqing","ror":"https://ror.org/011m1x742","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shixin Huang","raw_affiliation_strings":["Department of Scientific Research, The People's Hospital of Yubei District of Chongqing City, Chongqing, China","School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Scientific Research, The People's Hospital of Yubei District of Chongqing City, Chongqing, China","institution_ids":["https://openalex.org/I4210161892"]},{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130813551","display_name":"Yang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210089761","display_name":"West China Hospital of Sichuan University","ror":"https://ror.org/007mrxy13","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210089761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Chen","raw_affiliation_strings":["Department of Medical Ultrasound, West China Hospital, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medical Ultrasound, West China Hospital, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210089761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130754628","display_name":"Shuya Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shuya Lu","raw_affiliation_strings":["School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033430702","display_name":"Jiawei Luo","orcid":"https://orcid.org/0000-0003-1617-3224"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210089761","display_name":"West China Hospital of Sichuan University","ror":"https://ror.org/007mrxy13","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210089761"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiawei Luo","raw_affiliation_strings":["West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. 2111952576@qq.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. 2111952576@qq.com","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210089761"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5033430702"],"corresponding_institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210089761"],"apc_list":{"value":1570,"currency":"GBP","value_usd":1925},"apc_paid":{"value":1570,"currency":"GBP","value_usd":1925},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36593484,"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":0.9873999953269958,"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":0.9873999953269958,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.002300000051036477,"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/T10867","display_name":"Intensive Care Unit Cognitive Disorders","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2706","display_name":"Critical Care and Intensive Care 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/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.7329000234603882},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.7312999963760376},{"id":"https://openalex.org/keywords/saps-ii","display_name":"SAPS II","score":0.7260000109672546},{"id":"https://openalex.org/keywords/bonferroni-correction","display_name":"Bonferroni correction","score":0.6978999972343445},{"id":"https://openalex.org/keywords/retrospective-cohort-study","display_name":"Retrospective cohort study","score":0.6654999852180481},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.4327000081539154},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.43050000071525574},{"id":"https://openalex.org/keywords/intensive-care","display_name":"Intensive care","score":0.40880000591278076}],"concepts":[{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.7329000234603882},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7312999963760376},{"id":"https://openalex.org/C2777371824","wikidata":"https://www.wikidata.org/wiki/Q1457524","display_name":"SAPS II","level":4,"score":0.7260000109672546},{"id":"https://openalex.org/C127808970","wikidata":"https://www.wikidata.org/wiki/Q385989","display_name":"Bonferroni correction","level":2,"score":0.6978999972343445},{"id":"https://openalex.org/C167135981","wikidata":"https://www.wikidata.org/wiki/Q2146302","display_name":"Retrospective cohort study","level":2,"score":0.6654999852180481},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.566100001335144},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.4327000081539154},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.43050000071525574},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.41100001335144043},{"id":"https://openalex.org/C2987404301","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care","level":2,"score":0.40880000591278076},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C76318530","wikidata":"https://www.wikidata.org/wiki/Q16833590","display_name":"Area under the curve","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2806999981403351},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2800000011920929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27239999175071716},{"id":"https://openalex.org/C3020225094","wikidata":"https://www.wikidata.org/wiki/Q80091","display_name":"Area under curve","level":3,"score":0.27230000495910645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26919999718666077},{"id":"https://openalex.org/C187212893","wikidata":"https://www.wikidata.org/wiki/Q123028","display_name":"Pediatrics","level":1,"score":0.25839999318122864},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.2547000050544739}],"mesh":[{"descriptor_ui":"D000072878","descriptor_name":"Simplified Acute Physiology Score","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072878","descriptor_name":"Simplified Acute Physiology Score","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":"D000098417","descriptor_name":"Long Short Term Memory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098417","descriptor_name":"Long Short Term Memory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D007297","descriptor_name":"Inpatients","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D007297","descriptor_name":"Inpatients","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D007362","descriptor_name":"Intensive Care Units","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D007362","descriptor_name":"Intensive Care Units","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D007902","descriptor_name":"Length of Stay","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D007902","descriptor_name":"Length of Stay","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012720","descriptor_name":"Severity of Illness Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012720","descriptor_name":"Severity of Illness Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-026-03448-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03448-7","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:41896906","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41896906","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":null},{"id":"pmh:oai:doaj.org/article:e6e2690426eb48a3babcb6369bb0eda0","is_oa":true,"landing_page_url":"https://doaj.org/article/e6e2690426eb48a3babcb6369bb0eda0","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":"BMC Medical Informatics and Decision Making, Vol 26, Iss 1 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13147672","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13147672/","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/s12911-026-03448-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03448-7","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":[{"id":"https://metadata.un.org/sdg/1","score":0.6431267857551575,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2396881363","https://openalex.org/W2513134451","https://openalex.org/W2565892336","https://openalex.org/W2597505554","https://openalex.org/W2784499877","https://openalex.org/W2795884566","https://openalex.org/W2806031239","https://openalex.org/W2995685608","https://openalex.org/W3009583110","https://openalex.org/W3011812967","https://openalex.org/W3012690896","https://openalex.org/W3037480398","https://openalex.org/W3110388659","https://openalex.org/W3137590022","https://openalex.org/W3142654793","https://openalex.org/W3149054887","https://openalex.org/W3149221788","https://openalex.org/W3156901067","https://openalex.org/W3159743235","https://openalex.org/W3173148605","https://openalex.org/W3186283777","https://openalex.org/W3189722576","https://openalex.org/W4247943214","https://openalex.org/W4283025351","https://openalex.org/W4294001524","https://openalex.org/W4295678756","https://openalex.org/W4307405815","https://openalex.org/W4312058479","https://openalex.org/W4319968104","https://openalex.org/W4360999203"],"related_works":[],"abstract_inverted_index":{"OBJECTIVE:":[0],"To":[1],"evaluate":[2,115],"the":[3,40,78,88,96,104,154,176,185],"performance":[4,130,137,251],"fairness":[5,247,269],"of":[6,26,171],"a":[7],"long":[8],"short-term":[9,263],"memory":[10],"(LSTM)":[11],"model":[12,74,116,155,214,227,250],"in":[13,87,175,184,249],"predicting":[14],"in-hospital":[15,237],"mortality":[16],"for":[17,44,158],"inpatients":[18],"with":[19,160,196,216,225],"varying":[20],"severity,":[21],"as":[22,93],"reflected":[23],"by":[24],"length":[25],"stay":[27],"(LOS)":[28],"and":[29,65,81,110,123,143,163,182,199,208,219,254],"initial":[30],"clinical":[31],"scores.":[32,167,202],"MATERIALS":[33],"AND":[34,230],"METHODS:":[35],"This":[36],"retrospective":[37],"study":[38],"used":[39,113],"Medical":[41],"Information":[42],"Mart":[43],"Intensive":[45],"Care":[46],"(MIMIC)-IV":[47],"database,":[48],"which":[49],"includes":[50],"records":[51],"from":[52],"over":[53],"50,000":[54],"ICU":[55],"patients.":[56],"Patients":[57],"were":[58,112,126],"divided":[59],"into":[60],"subgroups":[61,86],"based":[62],"on":[63,77,84],"LOS":[64,142,162,180,198,207,218,253],"Simplified":[66],"Acute":[67],"Physiology":[68],"Score":[69],"(SAPS)":[70],"II.":[71],"The":[72,134,148,168,192],"LSTM":[73,135],"was":[75,151,173],"trained":[76],"training":[79],"set":[80],"then":[82],"tested":[83],"these":[85,268],"test":[89],"set.":[90],"Metrics":[91],"such":[92],"area":[94,102],"under":[95,103],"receiver":[97],"operating":[98],"characteristic":[99],"curve":[100,106],"(AUROC),":[101],"precision-recall":[105],"(AUPRC),":[107],"accuracy,":[108,215],"sensitivity,":[109],"specificity":[111],"to":[114,128,239],"performance.":[117,228],"Statistical":[118],"analyses,":[119],"including":[120],"logistic":[121],"regression":[122,204],"Bonferroni":[124],"correction,":[125],"conducted":[127],"compare":[129],"across":[131,252],"subgroups.":[132],"RESULTS:":[133],"model\u2019s":[136,193],"varied":[138],"significantly":[139,212],"among":[140],"different":[141],"SAPS":[144,165,188,200,209,221,255],"II":[145,166,189,201,210,222,256],"score":[146,190],"groups.":[147,257],"overall":[149],"AUROC":[150,170],"0.834,":[152],"but":[153],"performed":[156],"better":[157],"patients":[159],"shorter":[161],"lower":[164],"highest":[169],"0.931":[172],"observed":[174],"[12,":[177],"94)":[178],"hours":[179],"group,":[181],"0.811":[183],"[0,":[186],"25)":[187],"group.":[191],"accuracy":[194],"decreased":[195],"increasing":[197],"Logistic":[203],"confirmed":[205],"that":[206],"scores":[211,223],"affected":[213],"longer":[217],"higher":[220],"associated":[224],"poorer":[226],"DISCUSSION":[229],"CONCLUSION:":[231],"When":[232],"using":[233,262],"long-term":[234],"outcomes":[235,264],"like":[236],"death":[238],"build":[240],"early":[241],"assessment":[242],"models,":[243],"there":[244],"are":[245],"significant":[246],"issues":[248],"Developing":[258],"dynamic":[259],"prediction":[260],"models":[261],"may":[265],"help":[266],"reduce":[267],"issues.":[270]},"counts_by_year":[],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2026-03-28T00:00:00"}
