{"id":"https://openalex.org/W4400980763","doi":"https://doi.org/10.1186/s12911-024-02583-3","title":"Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury","display_name":"Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury","publication_year":2024,"publication_date":"2024-07-25","ids":{"openalex":"https://openalex.org/W4400980763","doi":"https://doi.org/10.1186/s12911-024-02583-3","pmid":"https://pubmed.ncbi.nlm.nih.gov/39054463"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-024-02583-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-024-02583-3","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02583-3","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","license_id":"https://openalex.org/licenses/cc-by","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://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02583-3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100642058","display_name":"Le Li","orcid":"https://orcid.org/0000-0002-6409-497X"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Li","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044379201","display_name":"Jingyuan Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyuan Guan","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032820759","display_name":"Xi Peng","orcid":"https://orcid.org/0000-0003-3809-5386"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Peng","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014668132","display_name":"Likun Zhou","orcid":"https://orcid.org/0009-0000-5216-5657"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Likun Zhou","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032035060","display_name":"Zhuxin Zhang","orcid":"https://orcid.org/0000-0001-6048-6610"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuxin Zhang","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066141242","display_name":"Ligang Ding","orcid":"https://orcid.org/0000-0002-5610-5974"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ligang Ding","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593353","display_name":"Lihui Zheng","orcid":"https://orcid.org/0000-0001-7361-7659"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihui Zheng","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102668264","display_name":"Lingmin Wu","orcid":"https://orcid.org/0009-0006-5180-4772"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingmin Wu","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077776876","display_name":"Zhicheng Hu","orcid":"https://orcid.org/0000-0002-3899-0711"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Hu","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388544","display_name":"Limin Liu","orcid":"https://orcid.org/0000-0003-2527-7201"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Limin Liu","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100619538","display_name":"Yan Yao","orcid":"https://orcid.org/0000-0003-0670-5338"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I4210161896","display_name":"Fu Wai Hospital","ror":"https://ror.org/0590dnz19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161896"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yao","raw_affiliation_strings":["Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China. ianyao@263.net.cn","Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China. ianyao@263.net.cn","institution_ids":["https://openalex.org/I4210161896","https://openalex.org/I200296433"]},{"raw_affiliation_string":"Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China","institution_ids":["https://openalex.org/I200296433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1570,"currency":"GBP","value_usd":1925},"apc_paid":{"value":1570,"currency":"GBP","value_usd":1925},"fwci":2.7239,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91035467,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"24","issue":"1","first_page":"208","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.7088000178337097,"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":0.7088000178337097,"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/T10684","display_name":"Acute Kidney Injury Research","score":0.16429999470710754,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"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":0.010099999606609344,"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/acute-kidney-injury","display_name":"Acute kidney injury","score":0.7636581659317017},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.6756365299224854},{"id":"https://openalex.org/keywords/sepsis","display_name":"Sepsis","score":0.6671673655509949},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.664751410484314},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.4510768949985504},{"id":"https://openalex.org/keywords/medical-emergency","display_name":"Medical emergency","score":0.44174638390541077},{"id":"https://openalex.org/keywords/emergency-medicine","display_name":"Emergency medicine","score":0.4358445405960083},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.3862021863460541},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3293679356575012},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2770506739616394},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.1963631808757782},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.18130242824554443}],"concepts":[{"id":"https://openalex.org/C2780472472","wikidata":"https://www.wikidata.org/wiki/Q424337","display_name":"Acute kidney injury","level":2,"score":0.7636581659317017},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.6756365299224854},{"id":"https://openalex.org/C2778384902","wikidata":"https://www.wikidata.org/wiki/Q183134","display_name":"Sepsis","level":2,"score":0.6671673655509949},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.664751410484314},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.4510768949985504},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.44174638390541077},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.4358445405960083},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.3862021863460541},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3293679356575012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2770506739616394},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.1963631808757782},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.18130242824554443}],"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":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":"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":"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":"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":"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":"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":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018805","descriptor_name":"Sepsis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D018805","descriptor_name":"Sepsis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D018805","descriptor_name":"Sepsis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D018805","descriptor_name":"Sepsis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D058186","descriptor_name":"Acute Kidney Injury","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D058186","descriptor_name":"Acute Kidney Injury","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D058186","descriptor_name":"Acute Kidney Injury","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D058186","descriptor_name":"Acute Kidney Injury","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-024-02583-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-024-02583-3","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02583-3","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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:39054463","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39054463","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:pubmedcentral.nih.gov:11271185","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11271185","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11271185/pdf/12911_2024_Article_2583.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:b9895e1d7e3a457885599b2929564569","is_oa":true,"landing_page_url":"https://doaj.org/article/b9895e1d7e3a457885599b2929564569","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 24, Iss 1, Pp 1-10 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s12911-024-02583-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-024-02583-3","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02583-3","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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400980763.pdf","grobid_xml":"https://content.openalex.org/works/W4400980763.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2006940889","https://openalex.org/W2026274122","https://openalex.org/W2026332974","https://openalex.org/W2102132939","https://openalex.org/W2122258831","https://openalex.org/W2143986203","https://openalex.org/W2149687213","https://openalex.org/W2159437578","https://openalex.org/W2234472895","https://openalex.org/W2280404143","https://openalex.org/W2396212074","https://openalex.org/W2396881363","https://openalex.org/W2520697268","https://openalex.org/W2550380542","https://openalex.org/W2586843379","https://openalex.org/W2949676527","https://openalex.org/W2950811882","https://openalex.org/W2999615587","https://openalex.org/W3094948551","https://openalex.org/W3121998102","https://openalex.org/W3135509762","https://openalex.org/W3190239739","https://openalex.org/W3216823933","https://openalex.org/W4214940323","https://openalex.org/W4224885775","https://openalex.org/W4233026002","https://openalex.org/W4282976375","https://openalex.org/W4321596088","https://openalex.org/W4383872084"],"related_works":["https://openalex.org/W3215560449","https://openalex.org/W3030236844","https://openalex.org/W2832459556","https://openalex.org/W4237737355","https://openalex.org/W4255354536","https://openalex.org/W2985696135","https://openalex.org/W4206554178","https://openalex.org/W2910674778","https://openalex.org/W3182723595","https://openalex.org/W4286005445"],"abstract_inverted_index":{"INTRODUCTION:":[0],"Sepsis-associated":[1],"acute":[2],"kidney":[3],"injury":[4],"(SA-AKI)":[5],"is":[6],"strongly":[7],"associated":[8],"with":[9,28,103,145,202],"poor":[10],"prognosis.":[11],"We":[12,115],"aimed":[13],"to":[14,22,36,66,82,110],"build":[15,111],"a":[16,176],"machine":[17],"learning":[18],"(ML)-based":[19],"clinical":[20,185],"model":[21,38,179],"predict":[23],"1-year":[24],"mortality":[25,199],"in":[26,200],"patients":[27,102,201],"SA-AKI.":[29,203],"METHODS:":[30],"Six":[31],"ML":[32,136],"algorithms":[33],"were":[34,80,91,108],"included":[35,109],"perform":[37],"fitting.":[39],"Feature":[40],"selection":[41],"was":[42,64],"based":[43,128,180],"on":[44,129,181],"the":[45,50,58,68,72,84,112,117,130,134,138,141,156,160,193],"feature":[46,131],"importance":[47],"evaluated":[48],"by":[49],"SHapley":[51],"Additive":[52],"exPlanations":[53],"(SHAP)":[54],"values.":[55],"Area":[56],"under":[57],"receiver":[59],"operating":[60],"characteristic":[61],"curve":[62,76],"(AUROC)":[63],"used":[65,184],"evaluate":[67],"discriminatory":[69],"ability":[70],"of":[71,100,148,153,197],"prediction":[73,89,113,143,178],"model.":[74],"Calibration":[75],"and":[77,95,105,125,150,174,190],"Brier":[78,151],"score":[79,127,152],"employed":[81],"assess":[83],"calibrated":[85],"ability.":[86],"Our":[87],"ML-based":[88,177],"models":[90],"validated":[92,175],"both":[93],"internally":[94],"externally.":[96],"RESULTS:":[97],"A":[98],"total":[99],"12,750":[101],"SA-AKI":[104],"55":[106],"features":[107,186],"models.":[114],"identified":[116],"top":[118],"10":[119,182],"predictors":[120],"including":[121],"age,":[122],"ICU":[123],"stay":[124],"GCS":[126],"importance.":[132],"Among":[133],"six":[135],"algorithms,":[137],"CatBoost":[139],"showed":[140],"best":[142],"performance":[144],"an":[146],"AUROC":[147],"0.813":[149],"0.119.":[154],"In":[155,169],"external":[157],"validation":[158],"set,":[159],"predictive":[161],"value":[162],"remained":[163],"favorable":[164],"(AUROC":[165],"=":[166],"0.784).":[167],"CONCLUSION:":[168],"this":[170],"study,":[171],"we":[172],"developed":[173],"commonly":[183],"which":[187],"could":[188],"accurately":[189],"early":[191],"identify":[192],"individuals":[194],"at":[195],"high-risk":[196],"long-term":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}