{"id":"https://openalex.org/W4390971041","doi":"https://doi.org/10.1109/bibm58861.2023.10385304","title":"Class-specific Prompts in Vision Transformer for Continual Learning of New Diseases","display_name":"Class-specific Prompts in Vision Transformer for Continual Learning of New Diseases","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390971041","doi":"https://doi.org/10.1109/bibm58861.2023.10385304"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/A5011215783","display_name":"Defeng Zhao","orcid":"https://orcid.org/0000-0002-8790-7283"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Defeng Zhao","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111080008","display_name":"Zejun Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zejun Ye","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108050904","display_name":"Wei\u2010Shi Zheng","orcid":"https://orcid.org/0000-0001-8327-0003"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Shi Zheng","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100707149","display_name":"Ruixuan Wang","orcid":"https://orcid.org/0000-0002-8714-0369"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixuan Wang","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","Department of Network Intelligence, Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, MOE, China","institution_ids":[]},{"raw_affiliation_string":"Department of Network Intelligence, Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011215783"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.8728,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79794459,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"994","last_page":"999"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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":0.9945999979972839,"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/T13410","display_name":"Immune responses and vaccinations","score":0.9617999792098999,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8171088695526123},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6524779796600342},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5851492881774902},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5496370792388916},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5242583751678467},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.42432814836502075},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4226337671279907},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42151951789855957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8171088695526123},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6524779796600342},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5851492881774902},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5496370792388916},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5242583751678467},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.42432814836502075},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4226337671279907},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42151951789855957},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2473930607","https://openalex.org/W2519210008","https://openalex.org/W2560647685","https://openalex.org/W2786446225","https://openalex.org/W2963559848","https://openalex.org/W2964189064","https://openalex.org/W2982220706","https://openalex.org/W2982410595","https://openalex.org/W3037492894","https://openalex.org/W3091175034","https://openalex.org/W3098511564","https://openalex.org/W3107810305","https://openalex.org/W3159650566","https://openalex.org/W3178686235","https://openalex.org/W3180392831","https://openalex.org/W3185341429","https://openalex.org/W4205941964","https://openalex.org/W4312238419","https://openalex.org/W4312351187","https://openalex.org/W4312468136","https://openalex.org/W4313525708","https://openalex.org/W4375843778","https://openalex.org/W6738602802","https://openalex.org/W6784333009","https://openalex.org/W6794876423"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W3172695526"],"abstract_inverted_index":{"Current":[0],"intelligent":[1,32],"diagnosis":[2],"systems":[3],"are":[4,102],"often":[5],"trained":[6],"to":[7,35,56,79],"diagnose":[8],"a":[9,70,81,94],"small":[10],"number":[11],"of":[12,18,43,51,96,121,156],"diseases":[13,54],"and":[14,59,72,83,147],"lack":[15],"the":[16,30,115,119,128,135,153,157],"ability":[17],"continually":[19,37,88],"learning":[20,28,75],"new":[21,45,90],"disease":[22,101,108],"knowledge.":[23],"To":[24],"have":[25],"such":[26,105],"continual":[27],"ability,":[29],"deployed":[31],"system":[33],"needs":[34],"be":[36,111],"updated":[38],"based":[39],"on":[40,142],"training":[41],"data":[42,50,62],"only":[44],"diseases,":[46],"without":[47],"accessing":[48],"old":[49],"previously":[52],"learned":[53,104],"due":[55],"privacy":[57],"concerns":[58],"challenges":[60],"in":[61,134],"sharing":[63],"across":[64],"medical":[65,144],"centers.":[66],"In":[67,92],"this":[68],"study,":[69],"novel":[71],"effective":[73],"prompt":[74],"strategy":[76],"is":[77,132,163],"proposed":[78,158],"help":[80],"pretrained":[82,133],"fixed":[84,116],"Vision":[85],"Transformer":[86],"(ViT)":[87],"learn":[89],"diseases.":[91],"particular,":[93],"set":[95],"unique":[97],"prompts":[98,122],"for":[99],"each":[100],"effectively":[103],"that":[106],"discriminative":[107],"features":[109],"can":[110],"well":[112],"extracted":[113],"from":[114],"ViT":[117,129],"under":[118],"instructions":[120],"during":[123],"feature":[124,130],"extraction,":[125],"even":[126],"though":[127],"extractor":[131],"natural":[136,149],"image":[137,145,150],"domain.":[138],"Extensive":[139],"empirical":[140],"evaluations":[141],"two":[143],"datasets":[146],"one":[148],"dataset":[151],"demonstrate":[152],"superior":[154],"performance":[155],"method.":[159],"The":[160],"source":[161],"code":[162],"available":[164],"at":[165],"https://github.com/zhaoedf/CSPrompt.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
