{"id":"https://openalex.org/W4293113278","doi":"https://doi.org/10.1145/3503823.3503912","title":"AI-driven prediction for the disposition of medium-risk incidents visiting emergency departments","display_name":"AI-driven prediction for the disposition of medium-risk incidents visiting emergency departments","publication_year":2021,"publication_date":"2021-11-26","ids":{"openalex":"https://openalex.org/W4293113278","doi":"https://doi.org/10.1145/3503823.3503912"},"language":"en","primary_location":{"id":"doi:10.1145/3503823.3503912","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503823.3503912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"25th Pan-Hellenic Conference on Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5013873489","display_name":"Smaranda Nafsika Ketseridou","orcid":"https://orcid.org/0000-0002-0304-4194"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Smaranda Nafsika Ketseridou","raw_affiliation_strings":["Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041636394","display_name":"Evangelos Logaras","orcid":"https://orcid.org/0000-0003-4921-3819"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Evangelos Logaras","raw_affiliation_strings":["Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065383087","display_name":"Antonis Billis","orcid":"https://orcid.org/0000-0002-1854-7560"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Antonis Billis","raw_affiliation_strings":["Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113880806","display_name":"Maria Zouka","orcid":null},"institutions":[{"id":"https://openalex.org/I2800980381","display_name":"AHEPA University Hospital","ror":"https://ror.org/01q1jaw52","country_code":"GR","type":"healthcare","lineage":["https://openalex.org/I2800980381"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Maria Zouka","raw_affiliation_strings":["AHEPA General University Hospital of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"AHEPA General University Hospital of Thessaloniki, Greece","institution_ids":["https://openalex.org/I2800980381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000029342","display_name":"Barbara Fyntanidou","orcid":"https://orcid.org/0000-0003-0019-0134"},"institutions":[{"id":"https://openalex.org/I2800980381","display_name":"AHEPA University Hospital","ror":"https://ror.org/01q1jaw52","country_code":"GR","type":"healthcare","lineage":["https://openalex.org/I2800980381"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Barbara Fyntanidou","raw_affiliation_strings":["AHEPA General University Hospital of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"AHEPA General University Hospital of Thessaloniki, Greece","institution_ids":["https://openalex.org/I2800980381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058926112","display_name":"Panagiotis D. Bamidis","orcid":"https://orcid.org/0000-0002-9936-5805"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Panagiotis Bamidis","raw_affiliation_strings":["Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Lab of Medical Physics &amp; Digital Innovation, Aristotle University of Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5013873489"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.2403,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62011943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"490","last_page":"494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11095","display_name":"Emergency and Acute Care Studies","score":0.9997000098228455,"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":0.9997000098228455,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9815000295639038,"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/T11467","display_name":"Trauma and Emergency Care Studies","score":0.9761000275611877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/triage","display_name":"Triage","score":0.7652904391288757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6938105821609497},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5982211828231812},{"id":"https://openalex.org/keywords/overcrowding","display_name":"Overcrowding","score":0.5590227246284485},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5360700488090515},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.47719085216522217},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4701419472694397},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4681834280490875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4575570821762085},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.4538707137107849},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4483564496040344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41829726099967957},{"id":"https://openalex.org/keywords/medical-emergency","display_name":"Medical emergency","score":0.25732579827308655},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17655622959136963}],"concepts":[{"id":"https://openalex.org/C2777120189","wikidata":"https://www.wikidata.org/wiki/Q780067","display_name":"Triage","level":2,"score":0.7652904391288757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938105821609497},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5982211828231812},{"id":"https://openalex.org/C2778872837","wikidata":"https://www.wikidata.org/wiki/Q7113614","display_name":"Overcrowding","level":2,"score":0.5590227246284485},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5360700488090515},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.47719085216522217},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4701419472694397},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4681834280490875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4575570821762085},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.4538707137107849},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4483564496040344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41829726099967957},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.25732579827308655},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17655622959136963},{"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","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":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503823.3503912","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503823.3503912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"25th Pan-Hellenic Conference on Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2038379663","https://openalex.org/W2144138337","https://openalex.org/W2155350701","https://openalex.org/W2295598076","https://openalex.org/W2564451347","https://openalex.org/W2624311461","https://openalex.org/W2752349109","https://openalex.org/W2788608859","https://openalex.org/W2810708119","https://openalex.org/W2884597820","https://openalex.org/W2903093159","https://openalex.org/W2911964244","https://openalex.org/W2929110666","https://openalex.org/W2984942011","https://openalex.org/W2997591727","https://openalex.org/W3165390445","https://openalex.org/W3180296548"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W1515008438","https://openalex.org/W3154586736","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487"],"abstract_inverted_index":{"Emergency":[0,54],"Departments":[1],"globally":[2],"suffer":[3],"overcrowding":[4],"due":[5],"to":[6,28,36,52,123,134,184,188],"the":[7,41,53,75,93,130,141,148,158,168,178],"lack":[8],"of":[9,31,45,77,86,89,92,153,162,171,177,180],"adequate":[10],"capacity":[11],"and/or":[12],"guidelines":[13],"and":[14,83,104,110,164],"policies":[15],"for":[16,74],"triaging":[17],"patients.":[18],"Medical":[19],"service":[20],"quality":[21],"improvement":[22],"requires":[23],"optimal":[24],"patient":[25,61],"prioritization":[26],"according":[27,51,183],"their":[29],"level":[30,49],"urgency.":[32],"This":[33],"study":[34],"aims":[35],"evaluate":[37],"classification":[38],"models":[39,190],"predicting":[40],"admission":[42],"or":[43],"discharge":[44],"incidents":[46],"triaged":[47],"as":[48],"3":[50],"Severity":[55],"Index":[56],"algorithm.":[57,138],"As":[58],"such,":[59],"adult":[60],"visits":[62],"were":[63,108],"examined":[64],"from":[65],"a":[66,84,120],"publicly":[67],"available":[68],"dataset.":[69],"Feature":[70],"Importance":[71],"was":[72,96,127],"used":[73],"assessment":[76,176],"each":[78],"variable":[79],"contribution":[80],"in":[81],"predictions":[82],"subset":[85],"196":[87],"out":[88],"972":[90],"variables":[91],"original":[94],"dataset":[95],"sampled.":[97],"XGBoost,":[98],"random":[99],"forest,":[100],"convolutional":[101],"neural":[102,116],"network,":[103],"k-nearest":[105],"neighbors":[106],"algorithms":[107,143],"deployed":[109],"evaluated":[111],"regarding":[112],"hospitalization":[113],"prediction.":[114],"Convolutional":[115],"network":[117],"utilization":[118],"required":[119],"tabular":[121],"data":[122],"image":[124],"transformation":[125],"which":[126,191],"applied":[128],"using":[129],"Image":[131],"Data":[132,136],"Generator":[133],"Tabular":[135],"(IGTD)":[137],"Benchmarking":[139],"among":[140],"four":[142],"showed":[144],"that":[145],"XGBoost":[146],"outperformed":[147],"others,":[149],"achieving":[150],"an":[151,155,165],"accuracy":[152],"0.75,":[154],"area":[156,166],"under":[157,167],"receiver":[159],"operating":[160],"curve":[161,170],"0.74":[163],"precision-recall":[169],"0.54.":[172],"Overall,":[173],"machine":[174],"learning-based":[175],"disposition":[179],"medium-risk":[181],"patients":[182],"ESI":[185],"may":[186],"lead":[187],"predictive":[189],"constitute":[192],"useful":[193],"decision":[194],"support":[195],"tools.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
