{"id":"https://openalex.org/W4391158892","doi":"https://doi.org/10.48550/arxiv.2401.12032","title":"MINT: A wrapper to make multi-modal and multi-image AI models interactive","display_name":"MINT: A wrapper to make multi-modal and multi-image AI models interactive","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391158892","doi":"https://doi.org/10.48550/arxiv.2401.12032"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2401.12032","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2401.12032","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078984106","display_name":"Jan Freyberg","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Freyberg, Jan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101502724","display_name":"Abhijit Guha Roy","orcid":"https://orcid.org/0000-0001-7221-468X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roy, Abhijit Guha","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090819649","display_name":"Terry Spitz","orcid":"https://orcid.org/0000-0002-9791-3767"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Spitz, Terry","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030669606","display_name":"Beverly Freeman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Freeman, Beverly","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025626087","display_name":"Mike Schaekermann","orcid":"https://orcid.org/0000-0002-1735-9680"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schaekermann, Mike","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064828134","display_name":"Patricia H. Strachan","orcid":"https://orcid.org/0000-0003-3121-4442"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Strachan, Patricia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078497529","display_name":"Eva Schnider","orcid":"https://orcid.org/0000-0002-0226-9519"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schnider, Eva","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060982337","display_name":"Renee Wong","orcid":"https://orcid.org/0009-0003-0403-7679"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Renee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060000122","display_name":"Dale R. Webster","orcid":"https://orcid.org/0000-0002-3023-8824"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Webster, Dale R","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003509342","display_name":"Alan Karthikesalingam","orcid":"https://orcid.org/0000-0001-5074-898X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karthikesalingam, Alan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078784976","display_name":"Yun Liu","orcid":"https://orcid.org/0000-0003-4079-8275"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050954769","display_name":"Krishnamurthy Dvijotham","orcid":"https://orcid.org/0000-0002-1328-4677"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dvijotham, Krishnamurthy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5084312082","display_name":"Umesh Telang","orcid":"https://orcid.org/0000-0003-0217-1885"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Telang, Umesh","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":78},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9879,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9879,"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.985,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9077,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.42565116}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.8177485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7198081},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6986817},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.56470364},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5490303},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.50491506},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.49555624},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46974808},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.42565116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3647042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3374393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32069206},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.17834154},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13611019},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2401.12032","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2401.12032","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2401.12032","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3013494979","https://openalex.org/W2515552481","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2168627904","https://openalex.org/W2095118173","https://openalex.org/W2058118494","https://openalex.org/W2015444353","https://openalex.org/W1570348318","https://openalex.org/W156769215"],"abstract_inverted_index":{"During":[0],"the":[1,11,42,55,85,91,182,220,236],"diagnostic":[2],"process,":[3],"doctors":[4,33],"incorporate":[5],"multimodal":[6],"information":[7,74],"including":[8],"imaging":[9],"and":[10,15,81,104,142,168,186,192,223,245,271],"medical":[12,17,37,117],"history":[13,38],"-":[14],"similarly":[16],"AI":[18,52,201],"development":[19],"has":[20],"increasingly":[21],"become":[22],"multimodal.":[23],"In":[24],"this":[25,247],"paper":[26],"we":[27,50,205,260],"tackle":[28],"a":[29,35,59,96,105,122,128,227,242],"more":[30,255],"subtle":[31],"challenge:":[32],"take":[34],"targeted":[36],"to":[39,53,110,126,147,175,218,266,276],"obtain":[40],"only":[41,84],"most":[43,76,86],"pertinent":[44],"pieces":[45,72],"of":[46,73,93,107,173,184,241],"information;":[47],"how":[48,246,262],"do":[49,54],"enable":[51],"same?":[56],"We":[57,89,131,150,177],"develop":[58],"wrapper":[60],"method":[61],"named":[62],"MINT":[63,94,134,158,180,232,263],"(Make":[64],"your":[65],"model":[66,281],"INTeractive)":[67],"that":[68,133,153,179,207,214],"automatically":[69],"determines":[70],"what":[71],"are":[75,119,140],"valuable":[77],"at":[78],"each":[79],"step,":[80],"ask":[82,148],"for":[83,250],"useful":[87],"information.":[88],"demonstrate":[90,152,261],"efficacy":[92],"wrapping":[95],"skin":[97],"disease":[98],"prediction":[99],"model,":[100],"where":[101],"multiple":[102,156],"images":[103],"set":[106],"optional":[108],"answers":[109],"$25$":[111],"standard":[112],"metadata":[113,138,185],"questions":[114],"(i.e.,":[115],"structured":[116],"history)":[118],"used":[120],"by":[121,190],"multi-modal":[123],"deep":[124],"network":[125],"provide":[127],"differential":[129],"diagnosis.":[130,228],"show":[132,206,231],"can":[135,159,211,233,272],"identify":[136,160],"whether":[137],"inputs":[139,188,210],"needed":[141,189],"if":[143,161,169],"so,":[144,170],"which":[145,171],"question":[146],"next.":[149],"also":[151],"when":[154],"collecting":[155],"images,":[157],"an":[162],"additional":[163],"image":[164,174,187],"would":[165],"be":[166,273],"beneficial,":[167],"type":[172],"capture.":[176],"showed":[178],"reduces":[181],"number":[183],"82%":[191],"36.2%":[193],"respectively,":[194],"while":[195],"maintaining":[196],"predictive":[197],"performance.":[198],"Using":[199],"real-world":[200],"dermatology":[202],"system":[203,221],"data,":[204],"needing":[208],"fewer":[209],"retain":[212],"users":[213],"may":[215],"otherwise":[216],"fail":[217],"complete":[219],"submission":[222],"drop":[224],"off":[225],"without":[226,279],"Qualitative":[229],"examples":[230],"closely":[234],"mimic":[235],"step-by-step":[237],"decision":[238],"making":[239],"process":[240],"clinical":[243],"workflow":[244],"is":[248,264],"different":[249,267],"straight":[251],"forward":[252],"cases":[253],"versus":[254],"difficult,":[256],"ambiguous":[257],"cases.":[258],"Finally":[259],"robust":[265],"underlying":[268],"multi-model":[269],"classifiers":[270],"easily":[274],"adapted":[275],"user":[277],"requirements":[278],"significant":[280],"re-training.":[282]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4391158892","counts_by_year":[],"updated_date":"2025-04-04T10:10:03.999579","created_date":"2024-01-24"}