{"id":"https://openalex.org/W4416663044","doi":"https://doi.org/10.1016/j.artmed.2025.103316","title":"Using artificial intelligence to predict patient wait times in the emergency department: A scoping review","display_name":"Using artificial intelligence to predict patient wait times in the emergency department: A scoping review","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W4416663044","doi":"https://doi.org/10.1016/j.artmed.2025.103316","pmid":"https://pubmed.ncbi.nlm.nih.gov/41313968"},"language":"en","primary_location":{"id":"doi:10.1016/j.artmed.2025.103316","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2025.103316","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence in Medicine","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.artmed.2025.103316","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120564873","display_name":"Troy Gloyn","orcid":null},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Troy Gloyn","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: tgloyn@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: tgloyn@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106367908","display_name":"Christina Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Christina Seo","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: cseo@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: cseo@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062315131","display_name":"Alexandra Godinho","orcid":"https://orcid.org/0000-0003-3430-1947"},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alexandra Godinho","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: agodinho@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: agodinho@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035736263","display_name":"Rahul Rahul","orcid":"https://orcid.org/0000-0001-7690-6704"},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rahul Rahul","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: rrahul@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: rrahul@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106367909","display_name":"Siona Phadke","orcid":null},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Siona Phadke","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: sphadke@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: sphadke@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120665203","display_name":"Hilary Fotheringham","orcid":null},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hilary Fotheringham","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: hfotheringham@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: hfotheringham@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083372597","display_name":"Pete Wegier","orcid":"https://orcid.org/0000-0003-0191-136X"},"institutions":[{"id":"https://openalex.org/I2802752716","display_name":"Humber River Regional Hospital","ror":"https://ror.org/02gj19t78","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I2802752716"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Pete Wegier","raw_affiliation_strings":["Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: pwegier@hrh.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Humber River Hospital Research Institute, 1235 Wilson Ave, North York, ON, M3M 0B2, Canada. Electronic address: pwegier@hrh.ca","institution_ids":["https://openalex.org/I2802752716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5120564873"],"corresponding_institution_ids":["https://openalex.org/I2802752716"],"apc_list":{"value":3230,"currency":"USD","value_usd":3230},"apc_paid":{"value":3230,"currency":"USD","value_usd":3230},"fwci":5.7111,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96382429,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"171","issue":null,"first_page":"103316","last_page":"103316"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11095","display_name":"Emergency and Acute Care Studies","score":0.44839999079704285,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"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/T11095","display_name":"Emergency and Acute Care Studies","score":0.44839999079704285,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency 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/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.27070000767707825,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.024700000882148743,"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/random-forest","display_name":"Random forest","score":0.715399980545044},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6245999932289124},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.48539999127388},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4526999890804291},{"id":"https://openalex.org/keywords/emergency-department","display_name":"Emergency department","score":0.3725999891757965},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33169999718666077},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.3260999917984009}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170000076293945},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.715399980545044},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6245999932289124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5669000148773193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.48539999127388},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C2780724011","wikidata":"https://www.wikidata.org/wiki/Q1295316","display_name":"Emergency department","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.28209999203681946},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2549000084400177}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003441","descriptor_name":"Crowding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003441","descriptor_name":"Crowding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003441","descriptor_name":"Crowding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003441","descriptor_name":"Crowding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003441","descriptor_name":"Crowding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000458","qualifier_name":"organization & administration","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000458","qualifier_name":"organization & administration","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000458","qualifier_name":"organization & administration","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000458","qualifier_name":"organization & administration","is_major_topic":true},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000458","qualifier_name":"organization & administration","is_major_topic":true},{"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":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014850","descriptor_name":"Waiting Lists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014850","descriptor_name":"Waiting Lists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014850","descriptor_name":"Waiting Lists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014850","descriptor_name":"Waiting Lists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014850","descriptor_name":"Waiting Lists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.artmed.2025.103316","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2025.103316","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence in Medicine","raw_type":"journal-article"},{"id":"pmid:41313968","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41313968","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":"Artificial intelligence in medicine","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.artmed.2025.103316","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2025.103316","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence in Medicine","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1954298792","https://openalex.org/W1976027422","https://openalex.org/W1976229405","https://openalex.org/W1978966005","https://openalex.org/W1983225075","https://openalex.org/W2054095862","https://openalex.org/W2077663548","https://openalex.org/W2146919434","https://openalex.org/W2169940017","https://openalex.org/W2414205703","https://openalex.org/W2617491945","https://openalex.org/W2962772482","https://openalex.org/W2964303497","https://openalex.org/W2986345464","https://openalex.org/W2991608839","https://openalex.org/W3015226707","https://openalex.org/W3093120355","https://openalex.org/W3099824897","https://openalex.org/W3135745777","https://openalex.org/W3194282783","https://openalex.org/W4200536500","https://openalex.org/W4251859756","https://openalex.org/W4280502440","https://openalex.org/W4313544936","https://openalex.org/W4322620306","https://openalex.org/W4364358787","https://openalex.org/W4385399619","https://openalex.org/W4386295480","https://openalex.org/W4388140989","https://openalex.org/W4388884267","https://openalex.org/W4389231539","https://openalex.org/W4393258421","https://openalex.org/W4393950709","https://openalex.org/W4408659328","https://openalex.org/W4410008242"],"related_works":[],"abstract_inverted_index":{"The":[0,60,226,340,432],"purpose":[1],"of":[2,11,18,119,130,169,203,217,267,275,306,322,342,381,442,449,456,462],"this":[3,79],"review":[4,177,319],"was":[5,152,192],"to":[6,77,88,109,134,199,243,259,357,389,425,458],"comprehensively":[7],"explore":[8],"the":[9,16,50,56,96,111,128,140,145,159,195,201,212,331,347,366,373,379,420,454,460,492,498],"landscape":[10],"recently":[12],"published":[13,183],"literature":[14,143],"on":[15,144,154,194,365,466,491],"applications":[17,118,321],"artificial":[19],"intelligence":[20],"(AI)":[21],"in":[22,28,55,125,139,180,324,330,361,371,496],"predicting":[23,325,408],"individualized":[24,135,326],"patient":[25,62,327,409,427,471],"waiting":[26,85,136,328,336,411],"times":[27,329,412,430,473],"an":[29,107,115],"emergency":[30],"department":[31],"(ED)":[32],"and":[33,39,52,63,66,74,90,121,171,186,223,237,280,292,296,308,369,416,476,494],"identify":[34],"pertinent":[35],"considerations":[36],"for":[37,176,246,407,469],"practitioners":[38],"hospital":[40],"decision-makers.":[41],"ED":[42,84,276,332,410,428,470],"overcrowding":[43,71],"is":[44,147,377,384,474,502],"being":[45],"experienced":[46],"by":[47,316],"hospitals":[48],"around":[49],"globe":[51],"has":[53],"worsened":[54],"post":[57],"COVID-19":[58],"era.":[59],"negative":[61],"staff":[64,91],"experiences":[65],"poor":[67],"clinical":[68],"outcomes":[69],"from":[70,106,211],"are":[72,92,396,419],"evident":[73],"necessitate":[75],"solutions":[76],"address":[78],"ongoing":[80],"problem.":[81],"Hospitals":[82],"providing":[83],"time":[86,137,337,375,500],"estimates":[87,314],"patients":[89],"becoming":[93],"popular;":[94],"however,":[95],"more":[97,274],"common":[98,204,422],"methods,":[99],"such":[100,345],"as":[101,346,386,439,446],"using":[102,158,254],"rolling":[103,312,404],"averages,":[104],"suffer":[105],"inability":[108],"capture":[110],"nuanced":[112],"relationships":[113],"within":[114],"ED.":[116],"Recent":[117],"AI":[120,188,285,307,323,399,467],"machine":[122],"learning":[123],"(ML)":[124],"healthcare":[126],"raises":[127],"possibility":[129],"applying":[131],"these":[132],"techniques":[133,262,401,423],"predictions":[138],"ED;":[141],"although,":[142],"topic":[146],"sparse.":[148],"A":[149],"systematized":[150],"search":[151,227],"conducted":[153],"November":[155],"10th,":[156],"2025,":[157],"electronic":[160],"databases":[161],"CINAHL,":[162],"EMBASE":[163],"(OVID),":[164,166],"Medline":[165],"PsychINFO,":[167],"Web":[168],"Science,":[170],"PubMed.":[172],"Articles":[173],"were":[174,209,240,252],"considered":[175],"if":[178,392],"written":[179],"English,":[181],"peer-reviewed,":[182],"after":[184,232],"2014,":[185],"used":[187,271,315,424],"techniques.":[189],"Descriptive":[190],"analysis":[191],"performed":[193],"final":[196,247],"extracted":[197],"data":[198,219,258],"facilitate":[200],"identification":[202],"themes":[205],"across":[206],"studies.":[207],"Themes":[208],"inferred":[210],"proportional":[213],"usage":[214],"among":[215,301],"studies,":[216],"different":[218],"preparation,":[220],"feature":[221,282,354],"selection,":[222],"modeling":[224,261,400,468],"strategies.":[225,339],"identified":[228,320,436],"8613":[229],"citations":[230],"that,":[231],"a":[233,265,387,447],"rigorous":[234],"screening":[235],"process":[236],"critical":[238],"appraisal,":[239],"narrowed":[241],"down":[242],"15":[244],"studies":[245,251,434,480],"review.":[248],"Most":[249],"included":[250,287],"observational,":[253],"historical":[255],"medical":[256],"record":[257],"compare":[260],"or":[263,273,351,394,484],"demonstrate":[264],"proof":[266],"concept.":[268],"Studies":[269],"commonly":[270],"one":[272],"queue-based,":[277],"staff/resource-based,":[278],"patient-based,":[279],"time-based":[281],"categories.":[283],"Incorporated":[284],"methods":[286,406],"Random":[288,348,414],"Forest,":[289],"Linear":[290],"Regression,":[291],"Least":[293],"Absolute":[294],"Shrinkage":[295],"Selection":[297],"Operator":[298],"(LASSO)":[299],"techniques,":[300,344],"several":[302],"others.":[303],"All":[304],"forms":[305],"ML":[309],"outperformed":[310],"traditional":[311,403],"average":[313,405],"hospitals.":[317],"This":[318],"that":[333,451],"outperform":[334,402],"current":[335],"estimate":[338,376,501],"use":[341],"nonlinear":[343],"Forest":[349],"method,":[350],"incorporating":[352],"queue-based":[353,437],"categories,":[355],"appeared":[356],"provide":[358],"better":[359],"performance":[360,486],"predictive":[362],"estimates.":[363],"Depending":[364],"end":[367],"user":[368],"modality":[370,493],"which":[372,497],"wait":[374,429,443,472,499],"conveyed,":[378],"importance":[380],"model":[382],"selection":[383],"highlighted":[385],"consideration":[388],"be":[390,488],"made":[391],"overestimates":[393],"underestimates":[395],"preferred.":[397],"\u2022":[398,413,431,464,481],"forests":[415],"linear":[417],"regression":[418],"most":[421],"predict":[426],"reviewed":[433],"consistently":[435],"features":[438,450],"significant":[440],"predictors":[441,457],"times,":[444],"or,":[445],"set":[448],"can":[452],"enrich":[453],"pool":[455],"improve":[459],"accuracy":[461],"predictions.":[463],"Literature":[465],"scarce":[475],"lacks":[477],"feasibility":[478],"implementation":[479],"Modeling":[482],"over-":[483],"under-":[485],"may":[487],"preferred":[489],"depending":[490],"end-user":[495],"used.":[503]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-05-25T08:39:21.599409","created_date":"2025-11-25T00:00:00"}
