{"id":"https://openalex.org/W4416553080","doi":"https://doi.org/10.1609/aaaiss.v7i1.36924","title":"Predicting Glucose Test Ordering in Hospitalized Patients Using Temporal Models of Clinical Context Embeddings","display_name":"Predicting Glucose Test Ordering in Hospitalized Patients Using Temporal Models of Clinical Context Embeddings","publication_year":2025,"publication_date":"2025-11-23","ids":{"openalex":"https://openalex.org/W4416553080","doi":"https://doi.org/10.1609/aaaiss.v7i1.36924"},"language":null,"primary_location":{"id":"doi:10.1609/aaaiss.v7i1.36924","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v7i1.36924","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/36924/39062","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/36924/39062","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120513862","display_name":"Joud El-Shawa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Joud El-Shawa","raw_affiliation_strings":["Vector Institute\nWestern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vector Institute\nWestern University","institution_ids":["https://openalex.org/I4210127509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075058250","display_name":"Elham Bagheri","orcid":"https://orcid.org/0000-0003-0434-8699"},"institutions":[{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Elham Bagheri","raw_affiliation_strings":["Vector Institute\nWestern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vector Institute\nWestern University","institution_ids":["https://openalex.org/I4210127509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010837853","display_name":"Amol A. Verma","orcid":"https://orcid.org/0000-0001-6857-931X"},"institutions":[{"id":"https://openalex.org/I4399598460","display_name":"Unity Health Toronto","ror":"https://ror.org/012x5xb44","country_code":null,"type":"healthcare","lineage":["https://openalex.org/I4399598460"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Amol Verma","raw_affiliation_strings":["Unity Health Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unity Health Toronto","institution_ids":["https://openalex.org/I4399598460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057801943","display_name":"Yalda Mohsenzadeh","orcid":"https://orcid.org/0000-0001-8525-957X"},"institutions":[{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yalda Mohsenzadeh","raw_affiliation_strings":["Vector Institute\nWestern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vector Institute\nWestern University","institution_ids":["https://openalex.org/I4210127509"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42262679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"1","first_page":"501","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11623","display_name":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","score":0.33959999680519104,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T11623","display_name":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","score":0.33959999680519104,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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":0.10119999945163727,"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/T11314","display_name":"Clinical Laboratory Practices and Quality Control","score":0.09650000184774399,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/context","display_name":"Context (archaeology)","score":0.6909000277519226},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.6315000057220459},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.510699987411499},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45719999074935913},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.39890000224113464},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3822999894618988},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.36640000343322754},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.3652999997138977}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6909000277519226},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.6315000057220459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6223999857902527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5967000126838684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5911999940872192},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.510699987411499},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35580000281333923},{"id":"https://openalex.org/C2910683987","wikidata":"https://www.wikidata.org/wiki/Q5572348","display_name":"Glucose test","level":3,"score":0.3472000062465668},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29660001397132874},{"id":"https://openalex.org/C120894424","wikidata":"https://www.wikidata.org/wiki/Q1322871","display_name":"Exploratory data analysis","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C98347192","wikidata":"https://www.wikidata.org/wiki/Q7705804","display_name":"Test score","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.26930001378059387},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaaiss.v7i1.36924","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v7i1.36924","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/36924/39062","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaaiss.v7i1.36924","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v7i1.36924","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/36924/39062","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416553080.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"overuse":[1],"of":[2,22,88,99,103,168,195],"laboratory":[3,184,196],"tests":[4,123],"is":[5,187],"a":[6,35,51,135,174,201],"persistent":[7],"challenge":[8],"in":[9,30,57,109,213],"healthcare,":[10],"driving":[11],"unnecessary":[12,210],"costs,":[13],"patient":[14],"discomfort,":[15],"and":[16,42,85,101,105,124,159,199],"low-value":[17],"care.":[18],"Glucose":[19],"testing,":[20],"one":[21],"the":[23,58,67,83,188,193],"most":[24],"common":[25],"diagnostics,":[26],"exemplifies":[27],"this":[28],"issue":[29],"hospital":[31],"settings.":[32],"We":[33],"present":[34],"deep":[36],"learning":[37],"framework":[38],"that":[39],"integrates":[40],"structured":[41],"unstructured":[43],"electronic":[44],"medical":[45],"record":[46],"data":[47,65],"to":[48,80,156,208],"predict":[49],"whether":[50],"glucose":[52,150],"test":[53,92,181,185,197],"will":[54],"be":[55],"ordered":[56],"next":[59],"AM/PM":[60],"time":[61],"bin.":[62],"Using":[63],"multi-hospital":[64],"from":[66],"GEMINI":[68],"dataset,":[69],"we":[70],"combine":[71],"Long":[72],"Short-Term":[73],"Memory":[74],"models":[75,115],"with":[76],"Clinical":[77],"BioBERT":[78],"embeddings":[79],"capture":[81],"both":[82],"timing":[84],"clinical":[86],"context":[87],"testing.":[89],"On":[90],"held-out":[91],"data,":[93],"our":[94],"best":[95],"model":[96],"achieved":[97,166],"ROC-AUC":[98],"0.92":[100],"PR-AUC":[102],"0.67,":[104],"generalized":[106],"across":[107],"sites":[108],"leave-one-hospital-out":[110],"evaluation":[111],"(ROC-AUC":[112],"0.84).":[113],"Embedding-based":[114],"outperformed":[116],"traditional":[117],"feature":[118],"representations,":[119],"though":[120],"adding":[121],"more":[122,177],"vitals":[125],"did":[126],"not":[127],"always":[128],"yield":[129],"further":[130],"gains.":[131],"By":[132],"contrast,":[133],"introducing":[134],"simple":[136],"temporal":[137],"recency":[138],"cue":[139],"(bin":[140],"counter)":[141],"improved":[142],"performance.":[143],"An":[144],"exploratory":[145],"regression":[146],"task":[147],"for":[148,176,203],"predicting":[149],"values":[151],"performed":[152],"worse,":[153],"likely":[154],"due":[155],"class":[157],"imbalance":[158],"reliance":[160],"on":[161],"forward-filled":[162],"values;":[163],"Random":[164],"Forest":[165],"R^2":[167],"0.80":[169],"under":[170],"masked":[171],"evaluation,":[172],"indicating":[173],"need":[175],"frequent":[178],"or":[179],"diverse":[180],"data.":[182],"Predicting":[183],"ordering":[186],"first":[189],"step":[190],"toward":[191],"evaluating":[192],"usefulness":[194],"use":[198,212],"establishes":[200],"foundation":[202],"future":[204],"real-time":[205],"decision":[206],"support":[207],"reduce":[209],"lab":[211],"hospitals.":[214]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-23T00:00:00"}