{"id":"https://openalex.org/W7146997525","doi":"https://doi.org/10.48550/arxiv.2603.27176","title":"MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence","display_name":"MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence","publication_year":2026,"publication_date":"2026-03-28","ids":{"openalex":"https://openalex.org/W7146997525","doi":"https://doi.org/10.48550/arxiv.2603.27176"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27176","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27176","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27176","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Park, Woohyeon","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Park, Woohyeon","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132674575","display_name":"Jaeik Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jaeik","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132688933","display_name":"Sunghwan Steve Cho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Sunghwan Steve","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059952027","display_name":"Pa Hong","orcid":"https://orcid.org/0000-0001-5495-5230"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Pa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132670130","display_name":"Wookyoung Jeong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeong, Wookyoung","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025698280","display_name":"Yoojin Nam","orcid":"https://orcid.org/0000-0001-8565-1360"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nam, Yoojin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129673024","display_name":"Namjoon Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Namjoon","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051502105","display_name":"Ginny Y. Wong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Ginny Y.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132654730","display_name":"Ka Chun Cheung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheung, Ka Chun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132680173","display_name":"Jaeyoung Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Jaeyoung","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.295199990272522,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.295199990272522,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.15770000219345093,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.1339000016450882,"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/discriminative-model","display_name":"Discriminative model","score":0.6452999711036682},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6432999968528748},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.49410000443458557},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4659000039100647},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.42010000348091125},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3328999876976013},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.32710000872612},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.31279999017715454}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6452999711036682},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6432999968528748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5004000067710876},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40849998593330383},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.38850000500679016},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3199999928474426},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2687000036239624},{"id":"https://openalex.org/C3018822202","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Patient data","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C3020672099","wikidata":"https://www.wikidata.org/wiki/Q857354","display_name":"Longitudinal data","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27176","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27176","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.27176","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27176","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7019726634025574,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Lesion":[0],"detection,":[1,132],"symptom":[2,133],"tracking,":[3,134],"and":[4,65,91,135,146,167,174],"visual":[5,113],"explainability":[6,99],"are":[7],"central":[8],"to":[9,60,87,104],"real-world":[10],"medical":[11,16],"image":[12,74],"analysis,":[13],"yet":[14],"current":[15],"Vision-Language":[17],"Models":[18],"(VLMs)":[19],"still":[20],"lack":[21],"mechanisms":[22],"that":[23,43,107,115,162],"translate":[24],"their":[25],"broad":[26],"knowledge":[27],"into":[28],"clinically":[29,40,168],"actionable":[30],"outputs.":[31],"To":[32],"bridge":[33],"this":[34],"gap,":[35],"we":[36],"present":[37],"MEDIC-AD,":[38],"a":[39,49,97],"oriented":[41],"VLM":[42],"strengthens":[44],"these":[45],"three":[46],"capabilities":[47],"through":[48],"stage-wise":[50],"framework.":[51],"First,":[52],"learnable":[53],"anomaly-aware":[54],"tokens":[55,76],"()":[56,77],"encourage":[57],"the":[58,85,102,119],"model":[59,86,103],"focus":[61],"on":[62,150],"abnormal":[63],"regions":[64],"build":[66],"more":[67],"discriminative":[68],"lesion":[69],"centered":[70],"representations.":[71],"Second,":[72],"inter":[73],"difference":[75],"explicitly":[78],"encode":[79],"temporal":[80],"changes":[81],"between":[82],"studies,":[83],"allowing":[84],"distinguish":[88],"worsening,":[89],"improvement,":[90],"stability":[92],"in":[93,171],"disease":[94],"burden.":[95],"Finally,":[96],"dedicated":[98],"stage":[100],"trains":[101],"generate":[105],"heatmaps":[106],"highlight":[108],"lesion-related":[109],"regions,":[110],"offering":[111],"clear":[112],"evidence":[114],"is":[116],"consistent":[117],"with":[118,142],"model's":[120],"reasoning.":[121],"Through":[122],"our":[123],"staged":[124],"design,":[125],"MEDIC-AD":[126,163],"steadily":[127],"boosts":[128],"performance":[129],"across":[130],"anomaly":[131,136],"segmentation,":[137],"achieving":[138],"state-of-the-art":[139],"results":[140],"compared":[141],"both":[143],"closed":[144],"source":[145],"medical-specialized":[147],"baselines.":[148],"Evaluations":[149],"real":[151,157],"longitudinal":[152],"clinical":[153],"data":[154],"collected":[155],"from":[156],"hospital":[158],"workflows":[159,176],"further":[160],"show":[161],"delivers":[164],"stable":[165],"predictions":[166],"faithful":[169],"explanations":[170],"practical":[172],"patient-monitoring":[173],"decision-support":[175]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-04-02T00:00:00"}
