{"id":"https://openalex.org/W7164998437","doi":"https://doi.org/10.48550/arxiv.2606.17474","title":"AIPatient Arena: EHR-grounded evaluation of large language models in end-to-end clinical consultation workflows","display_name":"AIPatient Arena: EHR-grounded evaluation of large language models in end-to-end clinical consultation workflows","publication_year":2026,"publication_date":"2026-06-16","ids":{"openalex":"https://openalex.org/W7164998437","doi":"https://doi.org/10.48550/arxiv.2606.17474"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.17474","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17474","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.17474","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138783507","display_name":"Jiahui Niu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Jiahui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138823331","display_name":"Huizi Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Huizi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053016868","display_name":"W. Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenkong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045374334","display_name":"Guangxin Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Guangxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054392745","display_name":"Jingxian He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Jingxian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138797077","display_name":"Xiang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138758845","display_name":"Zhiying Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Zhiying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125369856","display_name":"Xinxin Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Xinxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138815649","display_name":"Kent CY So","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"So, Kent CY","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138771558","display_name":"Bryan YP Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Bryan YP","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138779588","display_name":"Yun Kwok Wing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wing, Yun Kwok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138766504","display_name":"Yanqiu Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Yanqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138821465","display_name":"Xin Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138779856","display_name":"Lizhou Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Lizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6276000142097473,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6276000142097473,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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":0.18299999833106995,"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/T10028","display_name":"Topic Modeling","score":0.056299999356269836,"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/workflow","display_name":"Workflow","score":0.6212000250816345},{"id":"https://openalex.org/keywords/clarity","display_name":"CLARITY","score":0.6128000020980835},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.61080002784729},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5437999963760376},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4575999975204468},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.43209999799728394},{"id":"https://openalex.org/keywords/plain-language","display_name":"Plain language","score":0.41179999709129333},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.3393000066280365},{"id":"https://openalex.org/keywords/medline","display_name":"MEDLINE","score":0.3310000002384186}],"concepts":[{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6212000250816345},{"id":"https://openalex.org/C2777146004","wikidata":"https://www.wikidata.org/wiki/Q14949826","display_name":"CLARITY","level":2,"score":0.6128000020980835},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.61080002784729},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5437999963760376},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.41850000619888306},{"id":"https://openalex.org/C2777083192","wikidata":"https://www.wikidata.org/wiki/Q1814648","display_name":"Plain language","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40779998898506165},{"id":"https://openalex.org/C509550671","wikidata":"https://www.wikidata.org/wiki/Q126945","display_name":"Medical education","level":1,"score":0.3889000117778778},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3246000111103058},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3127000033855438},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.3100000023841858},{"id":"https://openalex.org/C3020452639","wikidata":"https://www.wikidata.org/wiki/Q454812","display_name":"Clinical judgment","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C2779328685","wikidata":"https://www.wikidata.org/wiki/Q1475557","display_name":"Patient safety","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C80059220","wikidata":"https://www.wikidata.org/wiki/Q7521302","display_name":"Simulated patient","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C42525527","wikidata":"https://www.wikidata.org/wiki/Q1209955","display_name":"Formative assessment","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C166151441","wikidata":"https://www.wikidata.org/wiki/Q4923601","display_name":"Causation","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C3019150057","wikidata":"https://www.wikidata.org/wiki/Q92779279","display_name":"Medical information","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C160798450","wikidata":"https://www.wikidata.org/wiki/Q4230870","display_name":"Concordance","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.17474","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17474","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.17474","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17474","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7299239039421082}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,214],"(LLMs)":[3],"are":[4],"increasingly":[5],"considered":[6],"for":[7,46,203,229],"use":[8],"in":[9,99,126,143,191],"clinical":[10,49,57,119,205],"consultation":[11],"tasks,":[12],"yet":[13],"most":[14],"medical":[15,100,174,234],"evaluations":[16],"remain":[17],"static,":[18],"single-turn,":[19],"or":[20],"narrowly":[21],"outcome-based,":[22],"limiting":[23],"their":[24],"ability":[25],"to":[26],"reflect":[27],"the":[28,48,209],"sequential,":[29],"uncertain,":[30],"and":[31,83,90,109,114,116,131,134,155,158,176,207,217],"interactive":[32],"nature":[33],"of":[34,51,56,80,88,118,145,172,179,211,233],"real-world":[35],"care.":[36],"Here,":[37],"we":[38],"propose":[39],"AIPatient":[40,74,223],"Arena,":[41],"an":[42,226],"EHRs-grounded":[43],"evaluation":[44,163,232],"framework":[45,60,228],"assessing":[47,212],"utility":[50],"LLMs":[52,96],"across":[53],"eight":[54],"dimensions":[55],"competence.":[58],"The":[59],"integrates":[61],"EHR":[62],"data":[63],"into":[64],"patient-specific":[65],"knowledge":[66],"graphs,":[67],"enabling":[68],"multi-turn":[69],"physician-patient":[70],"interactions.":[71],"We":[72,93],"applied":[73],"Arena":[75,224],"on":[76],"a":[77,221],"primary":[78],"cohort":[79],"437":[81],"patients":[82],"two":[84],"out-of-distribution":[85],"validation":[86],"cohorts":[87],"119":[89],"67":[91],"patients.":[92],"observe":[94],"that":[95,197],"performed":[97],"well":[98],"interview":[101],"questioning":[102],"skills":[103],"(QS;":[104],"mean":[105],"scores,":[106],"4.43-4.99/5),":[107],"ethical":[108],"professional":[110],"conduct":[111],"(ET;":[112],"4.38-4.93/5),":[113],"clarity":[115],"transparency":[117],"explanations":[120],"(EX;":[121],"3.80-4.72/5).":[122],"Performance":[123],"was":[124],"moderate":[125],"information":[127,151,219],"integration":[128],"(II;":[129],"3.19-4.21/5)":[130],"medication":[132],"safety":[133],"justification":[135],"(MS;":[136],"3.13-3.78/5),":[137],"but":[138,187],"persistent":[139],"weaknesses":[140],"were":[141],"observed":[142],"handling":[144,178],"ambiguous":[146],"patient":[147],"responses":[148],"(HR;":[149],"2.57-3.32/5),":[150],"coverage":[152],"(IC;":[153],"2.08-3.02/5),":[154],"diagnostic":[156,185],"accuracy":[157,199],"reasoning":[159,186],"(Dx;":[160],"2.63-3.55/5).":[161],"Process-based":[162],"revealed":[164],"recurrent":[165],"interaction":[166],"failures,":[167],"including":[168],"repetitive":[169],"questioning,":[170],"omission":[171],"past":[173],"history,":[175],"inadequate":[177],"uncertainty.":[180],"Richer":[181],"conversational":[182],"context":[183],"improved":[184],"yielded":[188],"limited":[189],"gains":[190],"treatment":[192],"planning.":[193],"These":[194],"findings":[195],"indicate":[196],"final-answer":[198],"alone":[200],"is":[201],"insufficient":[202],"evaluating":[204],"readiness":[206],"highlight":[208],"importance":[210],"how":[213],"gather,":[215],"interpret,":[216],"communicate":[218],"throughout":[220],"consultation.":[222],"provides":[225],"EHR-grounded":[227],"workflow-oriented":[230],"pre-deployment":[231],"LLMs.":[235]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-18T00:00:00"}