{"id":"https://openalex.org/W4390970087","doi":"https://doi.org/10.1109/bibm58861.2023.10385612","title":"Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records","display_name":"Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390970087","doi":"https://doi.org/10.1109/bibm58861.2023.10385612","pmid":"https://pubmed.ncbi.nlm.nih.gov/39055130"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11271049/pdf/nihms-2008001.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091243668","display_name":"Alex Moerschbacher","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alex Moerschbacher","raw_affiliation_strings":["Florida State University,School of Information,Tallahassee,United States","School of Information, Florida State University, Tallahassee, United States"],"affiliations":[{"raw_affiliation_string":"Florida State University,School of Information,Tallahassee,United States","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"School of Information, Florida State University, Tallahassee, United States","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047567293","display_name":"Zhe He","orcid":"https://orcid.org/0000-0003-3608-0244"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe He","raw_affiliation_strings":["Florida State University,School of Information,Tallahassee,United States","School of Information, Florida State University, Tallahassee, United States"],"affiliations":[{"raw_affiliation_string":"Florida State University,School of Information,Tallahassee,United States","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"School of Information, Florida State University, Tallahassee, United States","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5091243668"],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":1.2075,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83964817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2023","issue":null,"first_page":"4368","last_page":"4373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994999766349792,"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/T10198","display_name":"Heart Failure Treatment and Management","score":0.9916999936103821,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9585999846458435,"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/health-records","display_name":"Health records","score":0.7727193236351013},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.6832642555236816},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.5825322866439819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5736604332923889},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.4275703728199005},{"id":"https://openalex.org/keywords/emergency-medicine","display_name":"Emergency medicine","score":0.34998366236686707},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.34821927547454834},{"id":"https://openalex.org/keywords/medical-emergency","display_name":"Medical emergency","score":0.34782588481903076},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2924281358718872},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.25136619806289673},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2490783929824829},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.17905595898628235},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.07797941565513611}],"concepts":[{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.7727193236351013},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.6832642555236816},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.5825322866439819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5736604332923889},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.4275703728199005},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.34998366236686707},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.34821927547454834},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.34782588481903076},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2924281358718872},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.25136619806289673},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2490783929824829},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.17905595898628235},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.07797941565513611},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmid:39055130","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39055130","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":"Proceedings. IEEE International Conference on Bioinformatics and Biomedicine","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11271049","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11271049","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11271049/pdf/nihms-2008001.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings (IEEE Int Conf Bioinformatics Biomed)","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11271049","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11271049","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11271049/pdf/nihms-2008001.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings (IEEE Int Conf Bioinformatics Biomed)","raw_type":"Text"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[{"id":"https://openalex.org/G1900321182","display_name":null,"funder_award_id":"UL1TR001427","funder_id":"https://openalex.org/F4320309170","funder_display_name":"Florida State University"},{"id":"https://openalex.org/G2417061327","display_name":null,"funder_award_id":"UL1TR0014","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3328176752","display_name":null,"funder_award_id":"UL1TR00142","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3485779147","display_name":null,"funder_award_id":"R21AG061431","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G3497591915","display_name":null,"funder_award_id":"(NIH)","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4251098122","display_name":null,"funder_award_id":"UL1TR001427","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G4818037007","display_name":null,"funder_award_id":"TR001427","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4923956253","display_name":null,"funder_award_id":"R21AG061431","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7211153767","display_name":null,"funder_award_id":"UL1TR001427","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7757249039","display_name":null,"funder_award_id":"UL1TR00142","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"}],"funders":[{"id":"https://openalex.org/F4320309170","display_name":"Florida State University","ror":"https://ror.org/05g3dte14"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390970087.pdf"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2010620890","https://openalex.org/W2097548575","https://openalex.org/W2101234009","https://openalex.org/W2137080502","https://openalex.org/W2170131723","https://openalex.org/W2295598076","https://openalex.org/W2616680123","https://openalex.org/W2884499560","https://openalex.org/W2896457183","https://openalex.org/W2957430216","https://openalex.org/W2970641574","https://openalex.org/W2979826702","https://openalex.org/W3032899496","https://openalex.org/W3127548513","https://openalex.org/W3197477307","https://openalex.org/W6675354045","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W187932805","https://openalex.org/W2554558516","https://openalex.org/W4392490004","https://openalex.org/W1641026212","https://openalex.org/W4402738807","https://openalex.org/W2911982698","https://openalex.org/W2355354922","https://openalex.org/W2527724968","https://openalex.org/W2356296688","https://openalex.org/W4297688969"],"abstract_inverted_index":{"ICU":[0,58,90,148],"readmissions":[1],"are":[2,16],"associated":[3],"with":[4,26],"poor":[5,10],"outcomes":[6],"for":[7,146],"patients":[8,91],"and":[9,41,46,69,78,107,114,143],"performance":[11],"of":[12,22,53,66,89,118,132,139],"hospitals.":[13],"Patients":[14],"who":[15],"readmitted":[17,55],"have":[18,31],"an":[19,37,130],"increased":[20],"risk":[21,65],"in-hospital":[23,67],"deaths;":[24],"hospitals":[25],"a":[27,32,50],"higher":[28],"read-mission":[29],"rate":[30],"reduced":[33,42],"profitability,":[34],"due":[35],"to":[36,56,84],"increase":[38],"in":[39,92,124],"cost":[40],"payments":[43],"from":[44],"Medicare":[45],"Medicaid":[47],"programs.":[48],"Predicting":[49],"patient's":[51],"likelihood":[52],"being":[54],"the":[57,64,93,99,112,137],"can":[59],"help":[60,70],"reduce":[61],"early":[62],"discharges,":[63],"deaths,":[68],"in-crease":[71],"profitability.":[72],"In":[73],"this":[74,125],"study,":[75],"we":[76],"built":[77],"evaluated":[79,115],"multiple":[80],"machine":[81,141],"learning":[82,142,145],"models":[83],"predict":[85],"30-day":[86],"readmission":[87],"rates":[88],"MIMIC-III":[94],"database.":[95],"We":[96],"used":[97],"both":[98],"structured":[100],"data":[101],"including":[102],"demographics,":[103],"laboratory":[104],"tests,":[105],"comorbidities,":[106],"unstructured":[108],"discharge":[109],"summaries":[110],"as":[111],"predictors":[113],"different":[116],"combinations":[117],"features.":[119],"The":[120],"best":[121],"performing":[122],"model":[123],"study":[126,135],"Logistic":[127],"Regression":[128],"achieved":[129],"AUROC":[131],"75.7%.":[133],"This":[134],"shows":[136],"potential":[138],"leveraging":[140],"deep":[144],"predicting":[147],"readmissions.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}