{"id":"https://openalex.org/W4411846901","doi":"https://doi.org/10.1186/s12911-025-03025-4","title":"Mortality predicting models for patients with infective endocarditis: a machine learning approach","display_name":"Mortality predicting models for patients with infective endocarditis: a machine learning approach","publication_year":2025,"publication_date":"2025-07-01","ids":{"openalex":"https://openalex.org/W4411846901","doi":"https://doi.org/10.1186/s12911-025-03025-4","pmid":"https://pubmed.ncbi.nlm.nih.gov/40598016"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-025-03025-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-03025-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-03025-4","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://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-03025-4","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018314602","display_name":"Ziyang Yang","orcid":"https://orcid.org/0000-0002-6605-3987"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang Zi-yang","raw_affiliation_strings":["Department of Geriatric Cardiovascular, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geriatric Cardiovascular, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341303","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-5287-6050"},"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":"Wang Qi","raw_affiliation_strings":["Department of Cardiology, Fuwai Hospital, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cardiology, Fuwai Hospital, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050215381","display_name":"Xingyan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingyan Liu","raw_affiliation_strings":["Department of Biostatistics, University of North Carolina at Chapel Hill, Chaple Hill, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, University of North Carolina at Chapel Hill, Chaple Hill, NC, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109778039","display_name":"Haolin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haolin Li","raw_affiliation_strings":["Department of Biostatistics, University of North Carolina at Chapel Hill, Chaple Hill, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, University of North Carolina at Chapel Hill, Chaple Hill, NC, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109412487","display_name":"Shouhong Wang","orcid":"https://orcid.org/0000-0002-2624-6784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shouhong Wang","raw_affiliation_strings":["Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060562607","display_name":"Danqing Yu","orcid":"https://orcid.org/0000-0003-0785-3965"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Danqing Yu","raw_affiliation_strings":["Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. gdydq100@126.com","Department of Cardiovascular, Guangdong Cardiovascular Institute Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China. gdydq100@126.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. gdydq100@126.com","institution_ids":[]},{"raw_affiliation_string":"Department of Cardiovascular, Guangdong Cardiovascular Institute Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China. gdydq100@126.com","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074464132","display_name":"Xuebiao Wei","orcid":"https://orcid.org/0000-0002-1279-9441"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuebiao Wei","raw_affiliation_strings":["Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China. weixuebiao@163.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China. weixuebiao@163.com","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5018314602"],"corresponding_institution_ids":[],"apc_list":{"value":1570,"currency":"GBP","value_usd":1925},"apc_paid":{"value":1570,"currency":"GBP","value_usd":1925},"fwci":3.4902,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92728765,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"25","issue":"1","first_page":"229","last_page":"229"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11551","display_name":"Infective Endocarditis Diagnosis and Management","score":0.9739999771118164,"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/T11551","display_name":"Infective Endocarditis Diagnosis and Management","score":0.9739999771118164,"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/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/T10195","display_name":"Antimicrobial Resistance in Staphylococcus","score":0.00279999990016222,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"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/infective-endocarditis","display_name":"Infective endocarditis","score":0.7409201264381409},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.6473082900047302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47910216450691223},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.43131306767463684},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3766491115093231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3716801404953003},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.3545570373535156},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.2602154016494751},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.16667157411575317},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.13880375027656555}],"concepts":[{"id":"https://openalex.org/C2780176578","wikidata":"https://www.wikidata.org/wiki/Q2450598","display_name":"Infective endocarditis","level":2,"score":0.7409201264381409},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.6473082900047302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47910216450691223},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.43131306767463684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3766491115093231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3716801404953003},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.3545570373535156},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2602154016494751},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.16667157411575317},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.13880375027656555}],"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":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"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":"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":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004696","descriptor_name":"Endocarditis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D004696","descriptor_name":"Endocarditis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D004696","descriptor_name":"Endocarditis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D004696","descriptor_name":"Endocarditis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"descriptor_ui":"D004696","descriptor_name":"Endocarditis","qualifier_ui":"Q000401","qualifier_name":"mortality","is_major_topic":true},{"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":"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":"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":"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":"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":"D011379","descriptor_name":"Prognosis","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":"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":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"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},{"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":"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":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-025-03025-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-03025-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-03025-4","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:40598016","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40598016","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:78f7ea210e4c44ffbd1cbe3277c88e86","is_oa":true,"landing_page_url":"https://doaj.org/article/78f7ea210e4c44ffbd1cbe3277c88e86","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 25, Iss 1, Pp 1-9 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12220579","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12220579","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/s12911-025-03025-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-03025-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-03025-4","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":[{"score":0.7099999785423279,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320330743","display_name":"Guangzhou Municipal Science and Technology Bureau","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411846901.pdf","grobid_xml":"https://content.openalex.org/works/W4411846901.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1537066827","https://openalex.org/W1968114652","https://openalex.org/W1974847584","https://openalex.org/W2008056655","https://openalex.org/W2088252378","https://openalex.org/W2121947900","https://openalex.org/W2135046866","https://openalex.org/W2136332000","https://openalex.org/W2176331245","https://openalex.org/W2336573973","https://openalex.org/W2339823058","https://openalex.org/W2579858376","https://openalex.org/W2606622513","https://openalex.org/W2609216440","https://openalex.org/W2612585525","https://openalex.org/W2739194528","https://openalex.org/W2753869290","https://openalex.org/W2786519130","https://openalex.org/W2787894218","https://openalex.org/W2795053756","https://openalex.org/W2911964244","https://openalex.org/W2913508292","https://openalex.org/W2919115771","https://openalex.org/W2942123858","https://openalex.org/W2949055903","https://openalex.org/W2982920185","https://openalex.org/W2990297314","https://openalex.org/W3046880129","https://openalex.org/W3047509632","https://openalex.org/W3093391145","https://openalex.org/W3211070695","https://openalex.org/W4210634580","https://openalex.org/W4321377298","https://openalex.org/W4365142486","https://openalex.org/W4385624313","https://openalex.org/W4386153816","https://openalex.org/W4388696511","https://openalex.org/W4400106382"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"BACKGROUND:":[0],"Infective":[1],"endocarditis":[2],"(IE)":[3],"is":[4],"a":[5],"fatal":[6],"cardiovascular":[7],"disease":[8],"with":[9,26,93,100,172],"varied":[10],"clinical":[11],"manifestations":[12],"but":[13,29],"rapid":[14,187],"progression.":[15],"A":[16,71,88,169],"series":[17],"of":[18,90,180],"existing":[19],"risk":[20,170,188],"models":[21],"helped":[22],"identify":[23],"IE":[24,94,184],"patients":[25,92],"high":[27],"risk,":[28],"the":[30,76,98,112],"imperfect":[31],"predictive":[32,40,54],"performance":[33,85],"and":[34,67,104,117,147,166,190],"limited":[35],"application":[36],"called":[37],"for":[38,53,84,115,144],"better":[39],"systems.":[41],"METHODS:":[42],"The":[43,133],"single-centered,":[44],"retrospective":[45],"observational":[46],"study":[47],"applied":[48,128],"four":[49],"machine":[50,65,173],"learning":[51,174],"methods":[52],"model":[55,171],"construction:":[56],"LASSO":[57],"logistic":[58],"regression,":[59],"random":[60],"forest":[61],"(RF),":[62],"support":[63],"vector":[64],"(SVM),":[66],"k-nearest":[68],"neighbors":[69],"(KNN).":[70],"10-fold":[72],"cross-validated":[73],"area":[74],"under":[75],"receiver":[77],"operating":[78],"characteristic":[79],"curve":[80],"(AUC-ROC)":[81],"was":[82,126,176],"used":[83],"evaluation.":[86],"RESULTS:":[87],"total":[89,151],"1705":[91],"were":[95,136],"enrolled":[96],"in":[97,178,183],"study,":[99],"119":[101],"in-hospital":[102,116,146],"deaths":[103,106],"178":[105],"after":[107],"6-month":[108],"follow-up.":[109],"RF":[110,125,139],"achieved":[111],"highest":[113],"AUC-ROCs":[114],"six-month":[118,148],"mortality":[119,149],"prediction":[120,182],"(in-hospital:":[121],"0.83,":[122],"6-month:":[123],"0.85).":[124],"also":[127],"to":[129],"assess":[130],"variable":[131],"importance.":[132],"following":[134],"variables":[135],"selected":[137],"by":[138],"as":[140],"top":[141],"important":[142],"predictors":[143],"both":[145],"prediction:":[150],"bilirubin,":[152],"N-terminal":[153],"pro-B-type":[154],"natriuretic":[155],"peptide,":[156],"albumin,":[157],"diastolic":[158],"blood":[159,162],"pressure,":[160],"fasting":[161],"glucose,":[163],"uric":[164],"acid,":[165],"age.":[167],"CONCLUSIONS:":[168],"approach":[175],"integrated":[177],"purpose":[179],"prognosis":[181],"patients,":[185],"helping":[186],"stratification":[189],"in-time":[191],"management":[192],"clinically.":[193],"CLINICAL":[194],"TRIAL":[195],"NUMBER:":[196],"Not":[197],"applicable.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}