{"id":"https://openalex.org/W4415407701","doi":"https://doi.org/10.3233/faia250860","title":"Enhancing Zero-Shot Learning of Pathology Vision-Language Foundation Models in Tumour Malignancy Recognition","display_name":"Enhancing Zero-Shot Learning of Pathology Vision-Language Foundation Models in Tumour Malignancy Recognition","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415407701","doi":"https://doi.org/10.3233/faia250860"},"language":null,"primary_location":{"id":"doi:10.3233/faia250860","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250860","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia250860","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100411426","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0001-6117-6745"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["School of Computer Science, The University of Sydney"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Sydney","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023691565","display_name":"Usman Naseem","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Usman Naseem","raw_affiliation_strings":["School of Computing, Macquarie University"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100614820","display_name":"Jinman Kim","orcid":"https://orcid.org/0000-0001-5960-1060"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinman Kim","raw_affiliation_strings":["School of Computer Science, The University of Sydney"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Sydney","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100411426"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50104298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10862","display_name":"AI in cancer detection","score":0.9653000235557556,"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":0.9653000235557556,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9591000080108643,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9406999945640564,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/digital-pathology","display_name":"Digital pathology","score":0.5339000225067139},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5159000158309937},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4422999918460846},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.42410001158714294},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.3864000141620636},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.3815999925136566},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3686000108718872},{"id":"https://openalex.org/keywords/malignancy","display_name":"Malignancy","score":0.3677999973297119}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682999968528748},{"id":"https://openalex.org/C2777522853","wikidata":"https://www.wikidata.org/wiki/Q5276128","display_name":"Digital pathology","level":2,"score":0.5339000225067139},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5159000158309937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5092999935150146},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45339998602867126},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4431000053882599},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.42410001158714294},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3483999967575073},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2831000089645386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C544855455","wikidata":"https://www.wikidata.org/wiki/Q1070952","display_name":"Histopathology","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.25769999623298645},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia250860","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250860","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia250860","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250860","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-Language":[0],"Foundation":[1],"Models":[2],"(VLFMs)":[3],"demonstrate":[4,182],"promise":[5],"in":[6,14,46,189,203,207,226],"zero-shot":[7,47,152,191,224],"learning":[8,225],"through":[9],"joint":[10],"visual-textual":[11],"representations.":[12],"However,":[13],"histopathology":[15,102,179],"image":[16,153],"analysis,":[17],"their":[18],"effectiveness":[19],"is":[20],"limited":[21],"by":[22],"weak":[23],"image-text":[24,192],"alignment":[25],"due":[26],"to":[27,33],"coarse-grained":[28],"textual":[29],"descriptions":[30,92,109],"that":[31,73,183],"fail":[32],"capture":[34],"critical":[35],"fine-grained":[36],"visual":[37,123],"details.":[38],"This":[39,136],"misalignment":[40],"introduces":[41],"semantic":[42,134],"noise":[43],"and":[44,55,132,148,159,171,194,205],"imprecision":[45],"retrieval,":[48],"hindering":[49],"the":[50,210,216],"identification":[51],"of":[52,87,144,201,218],"relevant":[53],"cases":[54],"degrading":[56],"downstream":[57],"classification.":[58,154],"To":[59,155],"address":[60],"this,":[61],"we":[62,161],"introduce":[63],"Retrieval-based":[64],"De-noising":[65],"Causal":[66],"Language":[67],"Modelling":[68],"(RDCLM),":[69],"a":[70,83,94,100,104,118],"novel":[71],"framework":[72],"refines":[74],"noisy":[75],"retrieval":[76,139,164,193,219],"outputs":[77],"from":[78,110],"pathology":[79,105],"VLFMs.":[80],"RDCLM":[81,184],"constructs":[82],"pathology-specific":[84],"knowledge":[85,112],"base":[86],"fine-grained,":[88],"discriminative":[89],"tumour":[90],"malignancy":[91,195],"using":[93],"large":[95],"language":[96,120],"model":[97],"(LLM).":[98],"Given":[99],"query":[101],"image,":[103],"VLFM":[106],"retrieves":[107],"candidate":[108],"this":[111],"base.":[113],"Our":[114,228],"de-noising":[115,220],"module,":[116],"leveraging":[117],"frozen":[119],"model,":[121],"integrates":[122],"features":[124],"with":[125],"these":[126],"retrieved":[127],"texts,":[128],"filtering":[129],"irrelevant":[130],"content":[131],"enhancing":[133],"alignment.":[135],"significantly":[137,185],"improves":[138],"precision":[140],"(by":[141],"an":[142,198],"average":[143,199],"10%":[145],"across":[146,177],"datasets)":[147],"enables":[149],"more":[150],"accurate":[151],"further":[156],"bolster":[157],"performance":[158],"generalization,":[160],"propose":[162],"two":[163],"augmentation":[165],"strategies:":[166],"Retrieval":[167],"Negatives":[168],"Replacement":[169],"(RNR)":[170],"Description-wise":[172],"Shuffling":[173],"(DS).":[174],"Extensive":[175],"evaluations":[176],"four":[178],"cancer":[180],"datasets":[181],"outperforms":[186],"state-of-the-art":[187],"methods":[188],"both":[190],"classification,":[196],"achieving":[197],"improvement":[200],"12.7%":[202],"F1-score":[204],"9.6%":[206],"accuracy":[208],"over":[209],"second-best":[211],"competitor.":[212],"These":[213],"results":[214],"highlight":[215],"importance":[217],"for":[221],"advancing":[222],"VLFM-based":[223],"histopathology.":[227],"code":[229],"available":[230],"at:":[231],"https://github.com/xw18958/RDCLM":[232]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-22T00:00:00"}