{"id":"https://openalex.org/W7126104457","doi":"https://doi.org/10.1109/bibm66473.2025.11356961","title":"CTIS-QA: Clinical Template-Informed Slide-Level Question Answering for Pathology","display_name":"CTIS-QA: Clinical Template-Informed Slide-Level Question Answering for Pathology","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126104457","doi":"https://doi.org/10.1109/bibm66473.2025.11356961"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5077036802","display_name":"J. G. Lu","orcid":"https://orcid.org/0009-0007-2893-1770"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Lu","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124240400","display_name":"Ziniu Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziniu Qian","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100769850","display_name":"Yifu Li","orcid":"https://orcid.org/0000-0003-0602-8429"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifu Li","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069155721","display_name":"Y. Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhou","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033792432","display_name":"Bingzheng Wei","orcid":"https://orcid.org/0000-0001-6979-0459"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bingzheng Wei","raw_affiliation_strings":["ByteDance Inc.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc.,Beijing,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100851248","display_name":"Yan Xu","orcid":"https://orcid.org/0009-0007-8187-0276"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Xu","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5077036802"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84101124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2602","last_page":"2608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.3497999906539917,"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":0.3497999906539917,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3003000020980835,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.052000001072883606,"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/question-answering","display_name":"Question answering","score":0.6658999919891357},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6334999799728394},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5482000112533569},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.4724000096321106},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4453999996185303},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41990000009536743},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3804999887943268},{"id":"https://openalex.org/keywords/pathological","display_name":"Pathological","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.666700005531311},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6658999919891357},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6334999799728394},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5482000112533569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012999773025513},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4275999963283539},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41990000009536743},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.3962000012397766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3682999908924103},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3666999936103821},{"id":"https://openalex.org/C207886595","wikidata":"https://www.wikidata.org/wiki/Q1456138","display_name":"Pathological","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C2777522853","wikidata":"https://www.wikidata.org/wiki/Q5276128","display_name":"Digital pathology","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C206497026","wikidata":"https://www.wikidata.org/wiki/Q1753883","display_name":"SNOMED CT","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.259799987077713},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6250134996","display_name":null,"funder_award_id":"62371016,U23B2063,L222032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2194775991","https://openalex.org/W2329659234","https://openalex.org/W2944072352","https://openalex.org/W4385076068","https://openalex.org/W4392005379","https://openalex.org/W4395699794","https://openalex.org/W4402727946","https://openalex.org/W4402733589","https://openalex.org/W4403730271","https://openalex.org/W4406259916","https://openalex.org/W4410461169","https://openalex.org/W4413147798","https://openalex.org/W4413444236","https://openalex.org/W4414197206"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"large":[1,48],"language":[2,49],"models":[3,50,271],"(MLLMs)":[4],"have":[5,32],"demonstrated":[6],"strong":[7],"performance":[8],"in":[9,63],"patch-level":[10],"pathological":[11,99,149],"image":[12],"analysis;":[13],"however,":[14],"they":[15],"often":[16],"lack":[17],"the":[18,73,108,109,139,243],"holistic":[19],"perceptual":[20],"capability":[21],"necessary":[22],"for":[23,172],"comprehensive":[24,127],"Whole":[25],"Slide":[26],"Image":[27],"(WSI)":[28],"interpretation.":[29],"Recent":[30],"approaches":[31],"explored":[33],"constructing":[34],"slide-level":[35,261],"MLLMs":[36],"using":[37,153],"VQA":[38,181],"datasets":[39,54],"that":[40,79,125,201,227,265],"are":[41,157],"entirely":[42],"generated":[43],"from":[44,56,134,151,169],"pathology":[45,135],"reports":[46,152],"by":[47,107],"(LLMs).":[51],"However,":[52],"these":[53],"suffer":[55],"critical":[57],"limitations:":[58],"hallucinated":[59],"content,":[60],"information":[61],"leakage":[62],"question":[64],"stems,":[65],"clinically":[66,192],"irrelevant":[67],"or":[68],"visual":[69],"independent":[70],"questions,":[71],"and":[72,84,105,128,176,186,209,260,281],"omission":[74],"of":[75,111,131,141,165],"essential":[76],"diagnostic":[77,132,204,230,262],"features-issues":[78],"undermine":[80],"both":[81,279],"data":[82],"quality":[83],"clinical":[85,93],"validity.":[86],"In":[87,101],"this":[88],"paper,":[89],"we":[90,117,147],"introduce":[91],"a":[92,119,163,178,218,224],"diagnosis":[94],"template-based":[95],"pipeline":[96,143],"to":[97,160],"collect":[98],"information.":[100],"collaboration":[102],"with":[103],"pathologists":[104],"guided":[106],"College":[110],"American":[112],"Pathologists":[113],"(CAP)":[114],"Cancer":[115],"Protocols,":[116],"design":[118],"Clinical":[120],"Pathology":[121],"Report":[122],"Template":[123],"(CPRT)":[124],"ensures":[126],"standardized":[129],"extraction":[130],"elements":[133],"reports.":[136],"We":[137,214,275],"validate":[138],"effectiveness":[140],"our":[142],"on":[144,246,257],"TCGA-BRCA.":[145],"First,":[146],"extract":[148],"features":[150,156],"CPRT.":[154],"These":[155],"then":[158],"used":[159],"build":[161],"CTIS-Align,":[162],"dataset":[164],"80k":[166],"slide-description":[167],"pairs":[168],"804":[170],"WSIs":[171,185],"vision-language":[173],"alignment":[174],"training,":[175],"CTISBench,":[177],"rigorously":[179],"curated":[180],"benchmark":[182],"comprising":[183],"977":[184],"14,879":[187],"question-answer":[188],"pairs.":[189],"CTIS-Bench":[190,280],"emphasizes":[191],"grounded,":[193],"closed-ended":[194],"questions":[195],"(e.g.,":[196],"tumor":[197],"grade,":[198],"receptor":[199],"status)":[200],"reflect":[202],"real":[203],"workflows,":[205],"minimize":[206],"non-visual":[207],"reasoning,":[208],"require":[210],"genuine":[211],"slide":[212],"understanding.":[213],"further":[215],"propose":[216],"CTIS-QA,":[217],"Slide-level":[219],"Question":[220],"Answering":[221],"model,":[222],"featuring":[223],"dual-stream":[225],"architecture":[226],"mimics":[228],"pathologists'":[229],"approach.":[231],"One":[232],"stream":[233],"captures":[234],"global":[235],"slidelevel":[236],"context":[237],"via":[238],"clustering-based":[239],"feature":[240],"aggregation,":[241],"while":[242],"other":[244],"focuses":[245],"salient":[247],"local":[248],"regions":[249],"through":[250],"attention-guided":[251],"patch":[252],"perception":[253],"module.":[254],"Extensive":[255],"experiments":[256],"WSI-VQA,":[258],"CTIS-Bench,":[259],"tasks":[263],"show":[264],"CTIS-QA":[266,282],"consistently":[267],"outperforms":[268],"existing":[269],"state-of-the-art":[270],"across":[272],"multiple":[273],"metrics.":[274],"will":[276],"fully":[277],"release":[278],"as":[283],"open-source":[284],"resources.":[285]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}
