{"id":"https://openalex.org/W7141428085","doi":"https://doi.org/10.48550/arxiv.2603.24649","title":"MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows","display_name":"MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7141428085","doi":"https://doi.org/10.48550/arxiv.2603.24649"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.24649","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24649","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.2603.24649","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130722573","display_name":"Weixiang Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Weixiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shen, Chengzhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chengzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130776701","display_name":"Yanzhu Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yanzhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130745015","display_name":"Che Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Che","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130793737","display_name":"Junde Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Junde","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130726285","display_name":"Jiayuan Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Jiayuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Han, Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Li, Zongyue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zongyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wu, Jingpei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jingpei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130748526","display_name":"Min Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Min","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xu, Daguang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Daguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jin, Yueming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Yueming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wiestler, Benedikt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wiestler, Benedikt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Rueckert, Daniel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rueckert, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Pan, Jiazhen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiazhen","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8457000255584717,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8457000255584717,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.038600001484155655,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.013899999670684338,"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/medical-imaging","display_name":"Medical imaging","score":0.6484000086784363},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5885000228881836},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.450300008058548},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.43059998750686646},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.36489999294281006},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.3154999911785126}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796000003814697},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.6484000086784363},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5885000228881836},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.43059998750686646},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3492000102996826},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34700000286102295},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33160001039505005},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","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":0.3025999963283539},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.24649","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24649","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.2603.24649","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24649","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":"Industry, innovation and infrastructure","score":0.46356821060180664,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"imaging":[1,34,63,90,215],"benchmarks":[2],"often":[3],"evaluate":[4],"VLMs":[5],"on":[6,164],"pre-selected":[7],"2D":[8],"images,":[9],"slices,":[10,122],"crops,":[11],"or":[12,108,127],"patches,":[13],"making":[14],"evaluation":[15,59],"closer":[16],"to":[17],"visual":[18,43],"recognition.":[19],"Real":[20],"clinical":[21],"workflows":[22],"impose":[23],"a":[24,56,71,80,104,113,186],"different":[25],"burden:":[26],"readers":[27],"must":[28,154,198],"search":[29],"through":[30],"complete":[31,105,222],"studies,":[32,223],"operate":[33,88],"software,":[35],"navigate":[36],"across":[37],"slices":[38],"and":[39,41,82,96,116,139,190,204],"magnifications,":[40],"document":[42],"evidence":[44,131,220],"that":[45,51,170],"can":[46,217],"be":[47,156],"audited.":[48],"We":[49,167],"argue":[50],"this":[52],"evidence-producing":[53],"workflow":[54],"is":[55,132],"critical":[57],"missing":[58],"axis":[60],"for":[61,74],"medical":[62,89,214],"agents.":[64],"To":[65],"study":[66,107],"it,":[67],"we":[68],"introduce":[69],"MedFlowBench,":[70],"full-study":[72],"benchmark":[73],"VLM":[75],"agents,":[76],"together":[77],"with":[78],"MedOpenClaw,":[79],"controlled":[81],"replayable":[83],"runtime":[84],"in":[85],"which":[86],"agents":[87,193,216],"viewers":[91],"such":[92],"as":[93],"3D":[94],"Slicer":[95],"QuPath.":[97],"In":[98],"each":[99],"episode,":[100],"an":[101,148],"agent":[102],"inspects":[103],"radiology":[106],"whole-slide":[109],"pathology":[110],"image,":[111],"returns":[112],"task":[114],"answer,":[115],"submits":[117],"structured":[118],"evidence,":[119,160],"including":[120],"key":[121],"coordinates,":[123],"regions":[124],"of":[125],"interest,":[126],"lesion-state":[128],"fields.":[129],"This":[130],"automatically":[133],"checked":[134],"against":[135],"withheld":[136],"masks,":[137],"annotations,":[138],"labels.":[140],"Across":[141],"evaluated":[142],"models,":[143],"final":[144],"answer-only":[145],"scoring":[146],"gives":[147],"overly":[149],"optimistic":[150],"picture:":[151],"when":[152,183,196],"answers":[153,227],"also":[155],"supported":[157],"by":[158,176],"correct":[159],"performance":[161],"drops":[162],"substantially":[163],"complex":[165,187],"workflows.":[166],"further":[168],"find":[169],"adding":[171],"image-analysis":[172],"tools":[173],"does":[174],"not":[175],"itself":[177],"solve":[178],"the":[179],"problem.":[180],"Tools":[181],"help":[182],"they":[184,197],"make":[185],"procedure":[188],"simple":[189],"reliable,":[191],"but":[192],"still":[194],"struggle":[195],"choose":[199],"inputs,":[200],"manage":[201],"viewer":[202],"state,":[203],"verify":[205],"intermediate":[206],"outputs":[207],"over":[208],"multiple":[209],"steps.":[210],"MedFlowBench":[211],"exposes":[212],"whether":[213],"produce":[218],"auditable":[219],"from":[221,228],"rather":[224],"than":[225],"plausible":[226],"selected":[229],"images.":[230]},"counts_by_year":[],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2026-03-28T00:00:00"}