{"id":"https://openalex.org/W2332483358","doi":"https://doi.org/10.1109/embc.2014.6944181","title":"Predicting number of hospitalization days based on health insurance claims data using bagged regression trees","display_name":"Predicting number of hospitalization days based on health insurance claims data using bagged regression trees","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2332483358","doi":"https://doi.org/10.1109/embc.2014.6944181","mag":"2332483358","pmid":"https://pubmed.ncbi.nlm.nih.gov/25570549"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2014.6944181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6944181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100661771","display_name":"Yang Xie","orcid":"https://orcid.org/0000-0001-9456-1762"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yang Xie","raw_affiliation_strings":["Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007533806","display_name":"G. Schreier","orcid":"https://orcid.org/0000-0003-3724-4255"},"institutions":[{"id":"https://openalex.org/I132118926","display_name":"Austrian Institute of Technology","ror":"https://ror.org/04knbh022","country_code":"AT","type":"facility","lineage":["https://openalex.org/I132118926"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Gunter Schreier","raw_affiliation_strings":["AIT Austrian Institute of Technology GmbH, Graz, Austria"],"affiliations":[{"raw_affiliation_string":"AIT Austrian Institute of Technology GmbH, Graz, Austria","institution_ids":["https://openalex.org/I132118926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056490381","display_name":"David C. Chang","orcid":"https://orcid.org/0000-0002-1414-1280"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"David C. W. Chang","raw_affiliation_strings":["Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056621558","display_name":"Sandra Neubauer","orcid":null},"institutions":[{"id":"https://openalex.org/I132118926","display_name":"Austrian Institute of Technology","ror":"https://ror.org/04knbh022","country_code":"AT","type":"facility","lineage":["https://openalex.org/I132118926"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Sandra Neubauer","raw_affiliation_strings":["AIT Austrian Institute of Technology GmbH, Graz, Austria"],"affiliations":[{"raw_affiliation_string":"AIT Austrian Institute of Technology GmbH, Graz, Austria","institution_ids":["https://openalex.org/I132118926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013317847","display_name":"Stephen J. Redmond","orcid":"https://orcid.org/0000-0002-2630-5449"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Stephen J. Redmond","raw_affiliation_strings":["Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060602596","display_name":"Nigel H. Lovell","orcid":"https://orcid.org/0000-0003-1637-1079"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nigel H. Lovell","raw_affiliation_strings":["Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, UNSW Australia, Sydney, New South Wales","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100661771"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.24122097,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2014","issue":null,"first_page":"2706","last_page":"2709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12246","display_name":"Chronic Disease Management Strategies","score":0.9465000033378601,"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/T12246","display_name":"Chronic Disease Management Strategies","score":0.9465000033378601,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9275000095367432,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9014999866485596,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6777462959289551},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5480237007141113},{"id":"https://openalex.org/keywords/health-insurance","display_name":"Health insurance","score":0.5189940333366394},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5173839330673218},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5006811618804932},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.46995997428894043},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4508799612522125},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4445054233074188},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42435187101364136},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.3767082095146179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3628852367401123},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3206108510494232},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27353328466415405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17884856462478638},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.13940206170082092},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11591982841491699},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.10900208353996277},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.092522531747818}],"concepts":[{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6777462959289551},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5480237007141113},{"id":"https://openalex.org/C2983635472","wikidata":"https://www.wikidata.org/wiki/Q334911","display_name":"Health insurance","level":3,"score":0.5189940333366394},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5173839330673218},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5006811618804932},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.46995997428894043},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4508799612522125},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4445054233074188},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42435187101364136},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.3767082095146179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3628852367401123},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3206108510494232},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27353328466415405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17884856462478638},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.13940206170082092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11591982841491699},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.10900208353996277},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.092522531747818},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000293","descriptor_name":"Adolescent","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":"D000369","descriptor_name":"Aged, 80 and over","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002675","descriptor_name":"Child, Preschool","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006760","descriptor_name":"Hospitalization","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007223","descriptor_name":"Infant","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007231","descriptor_name":"Infant, Newborn","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007344","descriptor_name":"Insurance Claim Reporting","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000293","descriptor_name":"Adolescent","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":"D000369","descriptor_name":"Aged, 80 and over","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002675","descriptor_name":"Child, Preschool","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006760","descriptor_name":"Hospitalization","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007223","descriptor_name":"Infant","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007231","descriptor_name":"Infant, Newborn","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007344","descriptor_name":"Insurance Claim Reporting","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000293","descriptor_name":"Adolescent","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":"D000369","descriptor_name":"Aged, 80 and over","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002675","descriptor_name":"Child, Preschool","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006760","descriptor_name":"Hospitalization","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007223","descriptor_name":"Infant","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007231","descriptor_name":"Infant, Newborn","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007344","descriptor_name":"Insurance Claim Reporting","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2014.6944181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6944181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},{"id":"pmid:25570549","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25570549","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2031846064","https://openalex.org/W2032991527","https://openalex.org/W2048446706","https://openalex.org/W2125449110","https://openalex.org/W2143945764","https://openalex.org/W2148681431","https://openalex.org/W2152742787"],"related_works":["https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W2312753042","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W2621086889","https://openalex.org/W3174513558"],"abstract_inverted_index":{"Healthcare":[0],"administrators":[1],"worldwide":[2],"are":[3],"striving":[4],"to":[5,28,42,59,87],"both":[6],"lower":[7],"the":[8,14,61,97,108,117,121,128],"cost":[9],"of":[10,16,37,63,90,92,142,151,155,164],"care":[11,17],"whilst":[12],"improving":[13],"quality":[15],"given.":[18],"Therefore,":[19],"better":[20],"clinical":[21],"and":[22,104,126,147,153,167],"administrative":[23],"decision":[24,73],"making":[25],"is":[26],"needed":[27],"improve":[29],"these":[30,159],"issues.":[31],"Anticipating":[32],"outcomes":[33],"such":[34],"as":[35],"number":[36,62,91,141],"hospitalization":[38,64],"days":[39,65,93,143],"could":[40],"contribute":[41],"addressing":[43],"this":[44,47],"problem.":[45],"In":[46],"paper,":[48],"a":[49,67,71,135,139,149],"method":[50,113,137],"was":[51],"developed,":[52],"using":[53],"large-scale":[54],"health":[55],"insurance":[56,78],"claims":[57,105],"data,":[58],"predict":[60],"in":[66,94,96,116,157,172],"population.":[68,119],"We":[69],"utilized":[70],"regression":[72],"tree":[74],"algorithm,":[75],"along":[76],"with":[77],"claim":[79],"data":[80,106],"from":[81,107],"300,000":[82],"individuals":[83],"over":[84,134],"three":[85],"years,":[86],"provide":[88],"predictions":[89,133],"hospital":[95],"third":[98],"year,":[99],"based":[100],"on":[101],"medical":[102],"admissions":[103],"first":[109],"two":[110,162],"years.":[111],"Our":[112],"performs":[114],"well":[115],"general":[118],"For":[120],"population":[122],"aged":[123],"65":[124],"years":[125],"over,":[127],"predictive":[129],"model":[130],"significantly":[131],"improves":[132],"baseline":[136],"(predicting":[138],"constant":[140],"for":[144],"each":[145],"patient),":[146],"achieved":[148],"specificity":[150],"70.20%":[152],"sensitivity":[154],"75.69%":[156],"classifying":[158],"subjects":[160],"into":[161],"categories":[163],"'no":[165],"hospitalization'":[166],"'at":[168],"least":[169],"one":[170],"day":[171],"hospital'.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
